Iowa State University

Faculty in the BCB Graduate Program conduct research in all major research areas of computational molecular biology, including genomics, structural genomics, functional genomics, and computational systems biology, with access to some of the most modern experimental platforms. Many interdisciplinary research projects take place at Iowa State.

Below are brief descriptions of the research interests of the BCB faculty. Our faculty work together as core and associate members of the BCB graduate program, so students can be published as first author on their BCB-related research work in several publications over their PhD careers. Both core and associate members can be mentors (major professors) for BCB students. Associate members are identified below their names.

To View By Last Name: A B C D E F G H J L M N P R S T V W Y

To View by Research Area: Go here.

* Asterisked Faculty currently serve as major or co-major professors for BCB Students.

Dean Adams

Associate BCB Faculty Member

Education: Ph.D., SUNY at Stony Brook, 1999

Research Interests:

• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking--Theoretical and empirical studies of phenotypic change in ecology and evolution; statistical shape analysis (morphometrics); community organization and species interactions

Description: In the Adams lab our research is directed towards understanding how ecological and evolutionary forces generate and maintain phenotypic diversity. To do this we integrate computational, mathematical, statistical and quantitative morphological methods to examine ecological hypotheses from an evolutionary perspective. Our empirical work examines patterns of ecological and evolutionary morphology to understand species interactions, microevolution and community organization (largely in Plethodon salamanders). In our theoretical research, we develop new analytical tools for examining patterns of phenotypic variation. Current theoretical research focuses on developing analytical methods for assessing multivariate patterns of phenotypic change, such as are found in studies of plasticity, character divergence (and displacement) biomechanics, ontogenetics, local adaptation, and microevolution, and quantitative genetics.

Selected Publications:

• Adams, D.C. 2008. Phylogenetic meta-analysis. Evolution. 62:567-572.
• Adams, D.C., and J.O. Church. 2008. Amphibians do not follow Bergmann’s rule. Evolution. 62:413-420.
• Adams, D.C. 2007. Organization of Plethodon salamander communities: guild-based community assembly. Ecology. 88:1292-1299.
• Adams, D.C., and M.L. Collyer. 2007. Analysis of character divergence along environmental gradients and other covariates. Evolution.61:510-515.
• Collyer, M.L., and D.C. Adams. 2007. Analysis of two-state multivariate phenotypic change in ecological studies. Ecology. 88:683-692.
• Adams, D.C., M.E. West, and M.L. Collyer. 2007. Location-specific sympatric morphological divergence as a possible response to species interactions in West Virginia Plethodon salamander communities. Journal of Animal Ecology. 76:289-295.
• Adams, D.C., and M.M. Cerney. 2007. Quantifying biomechanical motion using Procrustes motion analysis. Journal of Biomechanics. 40:437-444.
• Maerz, J. C., E. M. Myers, and D. C. Adams. 2006. Trophic polymorphism in a terrestrial salamander. Evolutionary Ecology Research. 8:23-35.
• Adams, D. C. 2004. Character displacement via aggressive interference in Appalachian salamanders. Ecology. 85:2664-2670.
• Adams, D. C., and F. J. Rohlf. 2000. Ecological character displacement in Plethodon: biomechanical differences found from a geometric morphometric study. Proceedings of the National Academy of Sciences, U.S.A. 97:4106-4111.

Vita: Click here to download

Website: Dean Adams

*Srinivas Aluru

Education: Ph.D., Iowa State, 1994

Research Interests: Computational and comparative genomics, systems biology, parallel computational biology, and string algorithms.

• Bioinformatics: Sequential/parallel algorithms and software systems for bioinformatics, with emphasis on EST clustering, sequence alignments, sequence databases and protein structure

Selected Publications:

• B. Jackson, P.S. Schnable and S. Aluru, "Consensus genetic maps as median orders from
  inconsistent sources," ACM/IEEE Transactions on Computational Biology and Bioinformatics, in
  press.
• A. Kalyanaraman, S.J. Emrich, P.S. Schnable and S. Aluru, "Assembling genomes on large-scale
  parallel computers," Journal of Parallel and Distributed Computing, Vol. 67, pp. 1240-1255, 2007.
• S.J. Emrich, L. Li, T.-J. Wen, M.D. Yandeau-Nelson, Y. Fu, L. Guo, H.-H. Chou, S. Aluru, D.A.
  Ashlock and P.S. Schanble, "Nearly identical paralogs (NIPs): implications for maize (Zea mays L.) genome evolution," Genetics, Vol. 175, pp. 429-439, 2007. (featured in Science, Vol. 315, No.
  5810, pp. 302 in Editor's Choice: Highlights of the recent literature).
• M. Ott, J. Zola, S. Aluru and A. Stamatakis, "Large-scale maximum-likelihood based phylogenetic
  analysis on the IBM Blue Gene/L," ACM/IEEE Supercomputing Conference, 2007. (best paper
  finalist)
• P. Ko and S. Aluru, "Optimal self-adjusting suffix tree layout for dynamic string data in secondary
  storage," Proc. 14th Symposium on String Processing and Information Retrieval (SPIRE),
  Springer Verlag Lecture Notes in Computer Science, Vol. 4726, pp. 184-194, 2007.
• J. Zola, X. Yang, A. Rospondek and S. Aluru, "Parallel-TCoffee: A parallel multiple sequence
  aligner," Proc. ISCA Parallel and Distributed Computing Systems (PDCS), pp. 248-253, 2007.
• S. Emrich, A. Kalyanaraman and S. Aluru, "Massively parallel expressed sequence tag
  clustering," Proc. ISCA Parallel and Distributed Computing Systems (PDCS), pp. 254-261,
  2007.
• S. Aluru, N. Amato and D.A. Bader, "Editorial: Special section on high performance
  computational biology," IEEE Transactions on Parallel and Distributed Systems, Vol. 17, No. 8,
  pp. 737-740, 2006.
• A. Kalyanaraman and S. Aluru, "Efficient algorithms and software for detection of full-length LTR
  retrotransposons,'' Journal of Bioinformatics and Computational Biology, Vol. 4, No. 2, pp. 197-
  216, 2006.
• S. Seal and S. Aluru, "Communication-aware parallel domain decomposition using space-filling
  curves," ISCA 19th International Conference on Parallel and Distributed Computing Systems
  (PDCS), pp. 159-164, 2006.
• A. Kalyanaraman, S. Aluru and P.S. Schnable, "Turning repeats to advantage: scaffolding
  genomic contigs using LTR retrotransposons," Proc. Life Sciences Society Computational
  Systems Bioinformatics (CSB) Conference, pp. 167-178, 2006.

Vita: Click here to download

Website: Srinivas Aluru

*Amy Andreotti

Education: Ph.D., Princeton, 1994

Research Interests: Macromolecular structure-function, NMR spectroscopy

• Macromolecular Structure and Function--Macromolecular structure/function relationships; protein structure determination using nuclear magnetic resonance; molecular recognition

Description:

Selected Publications:

• R.E. Joseph, A.H. Andreotti , Bacterial expression and purification of interleukin-2 tyrosine kinase: single step separation of the chaperonin impurity. Protein Expr Purif., 60, 194-7 (2008).

• A. Severin, D.B. Fulton, A.H. Andreotti, Murine Itk SH3 domain. J Biomol NMR.40, 285-90 (2008).

• R.E. Joseph, D.B. Fulton, A.H. Andreotti. Mechanism and functional significance of Itk autophosphorylation. J Mol Biol ., 373, 1281-92 (2007).

• R.E. Joseph, L. Min, A.H. Andreotti, The linker between SH2 and kinase domains positively regulates catalysis of the Tec family kinases, Biochemistry, 46, 5455-62 (2007).

• R.E. Joseph, L. Min, R. Xu, E. Musselman, A.H. Andreotti, A remote substrate-docking mechanism for the Tec family tyrosine kinases, Biochemistry 46, 5595-603 (2007).

• Huang, Y.H., Grasis, J.A., Miller, A.T., Xu, R., Soonthronvacharin, S., Andreotti, A.H., Tsoukas, C.D., Cooke, M.P. & Sauer, K. Positive regulation of Itk PH domain function by soluble IP4, Science, 316, 886-9 (2007).

• E. Pletneva, M. Sundd, D.B. Fulton & A.H. Andreotti, Molecular details of Itk activation by prolyl isoemrization and phospholigand binding: the NMR structure of the Itk SH2 domain bound to a phosphopeptide, J. Mol. Biol., 357, 550-561 (2006).

• A.H. Andreotti Opening the pore hinges on proline. Nat Chem Biol., 2, 13-14 (2006).

• D.V. Venkitaramani, D.B. Fulton, A.H. Andreotti, K.M. Johansen, J. Johansen, Mapping the Ca2+ -dependent binding of an invertebrate homolog of protein phosphatase 4 regulatory subunit 2 to the small EF-hand protein, calsensin. Biochim Biophys Acta. 1763, 322-329 (2006).

Vita: Click here to download

Website: Amy Andreotti

Lyric Bartholomay

Associate BCB Faculty Member

Education: Ph.D., University of Wisconsin-Madison, 2004

Research Interests:

• In describing and understanding the interactions between mosquitoes and the pathogens they transmit to prevent transmission of vector-borne diseases, my lab employs bioinformatics/computational biology - we use bioinformatics (EST sequencing, genome mining, etc.) and functional genomics tools (microarrays), in which I was trained in my Doctoral and Postdoctoral work.

Selected Publications:

• Beerntsen, BT, Bartholomay, LC, Lowery, RJ. 2007. Penetration of the mosquito midgut is not required for Brugia pahangi microfilariae to avoid the melanotic encapsulation response of Armigeres subalbatus. Veterinary Parasitology 144: 371-374.
• Platt KB, Tucker BJ, Halbur PG, Tiawsirisup S, Blitvich BJ, Fabiosa FG, Bartholomay, LC, Rowley , WA . 2007. West Nile virus viremia in eastern chipmunks (Tamias striatus) sufficient for infecting different mosquitoes. Emerg Infect Dis. 13(6) 831-837.
• Oliver, J, Holscher, K, Hutcheson, HJ, Bartholomay, LC. Ticks and tick-borne diseases in Iowa. 6 pp. Iowa State University Extension Publications PM2036.
• Waterhouse, RM, Kriventseva, EV, Meister, S, Xi, ZY, Alvarez, KS, Bartholomay, LC, Barillas-Mury, C, Bian, G, Blandin, S, Christensen, BM, Dong, Y, Jiang, H, Kanost, M, Koutsos, AC, Levashina, E A, Li, J, Ligoxygakis, P, MacCallum, MR, Mayhew, GF, Mendes, A, Michel, K, Osta, MA, Paskewitz, S, Shin, SW, Vlachou, D, Wang, L. Wei, W, Zheng, L, Zou, Z, Severson, DW, Raikhel, A, Kafatos, FC, Dimopoulos, G, Zdobnov, EM, Christophides, GK. 2007. Evolutionary Dynamics of Immune-Related Genes and Pathways in Disease-Vector Mosquitoes. Science. [in press]

Vita: Click here to download

Website: New Faculty

*William Beavis

Education: Ph.D., 1986, Plant Breeding, Iowa State University, Ames, IA

Research Interests:

• Theoretically, the impact of genetic bottlenecks is through selection, drift and disequilibrium which limit genetic potential of a crop to sub-optimal levels (Robertson, 1960; Hill and Robertson, 1968; Bulmer, 1971). Despite theoretical considerations of limits to genetic potential, we do not know: 1) whether desirable allelic variants have been eliminated during the adaptation and breeding processes, 2) how to distinguish desirable and undesirable allelic variants in unadapted germplasm, and 3) if desirable alleles can be identified, how do we recover them without sacrificing genetic gains made by previous generations of breeders? 
  Until the emergence of genomics and high throughput genotyping technologies, these types of questions could not be addressed on an experimental basis. Thus, theories developed over 50 years ago have not been tested and modified. We use the tools of genomics, bioinformatics, population genetics, quantitative genetics and modeling to address these questions.  Explicitly, we are developing: 1) experimental strategies for identifying desirable alleles in unadapted germplasm 2) methods to predict the value of desirable alleles, 3) optimal breeding strategies for migrating desirable alleles from unadapted germplasm into elite breeding populations without sacrificing established genetic gains and 4)computational tools to recognize genomic signatures of breeding populations with sub-optimal limits to selection. The impact of addressing these challenges experimentally and analytically will assure that the full genetic potential of maize can be realized using the most effective genetic resources and efficient breeding methods.  From an academic perspective this project also will begin the process of integrating discoveries from genomics with theoretical models of population and quantitative genetics.

Selected Publications:

• Kingsmore, SF, IE Lindquist, J Mudge, DD Gesler, WD Beavis (2008) Genome-wide association studies: progress and potential for drug discovery and development. Nature Reviews (adv online publication) doi:10.1038/nrd2519

• Kingsmore, SF, IE Lindquist, J Mudge WD Beavis (2007) Genome-Wide Association Studies: Progress in Identifying Genetic Biomarkers in Common, Complex Diseases. Biomarker Insights 2007:2 1–10.

• Beavis, WD , FD Schilkey, SM Baxter (2007). Translational Bioinformatics: At the Interface of Genomics and Quantitative Genetics. Crop Science 47(s3): 32-43

• Gonzales, MD, K Gajendran, AD Farmer, E Archuleta, WD Beavis (2007) Leveraging model legume information to find candidate genes for soybean Sudden Death Syndrome using the Legume Information System (LIS). In Ed. Edwards D. Methods in Molecular Biology , Humana Press ( USA), pp. 245-260

• Stein, L, DD Gessler, D Rokshar, D Main, L Mueller, E Huala, C Lawrence, S Rhee, WD Beavis (2006) Save our Data. The Scientist April 24-25.

• Beavis, WD . (2005) Architectures for Integration of Data and Applications: Lessons from Integration Projects. In Genome Exploration:Data Mining and the Genome. The Stadler Genetics Symposia XXII:.Springer (eds. P. Gustafson, R. Shoemaker and J.W. Snape) pp. 31-46

• Gepts, P. WD Beavis, EC Brummer, RC Shoemaker, HT Stalker, NF Weeden, ND Young. (2005) Legumes as a Model Plant Family: Genomics for Food and Feed. Report of the Cross Legume Advances through Genomics Conference. Plant Physiology 137: 1228-1235.

Vita: Click here to download

Website: William Beavis

Madan Bhattacharyya

Education: Ph.D., Western Ontario, 1987

Research Interests: Functional genomic and proteomic approaches to disease resistance and susceptibility

• Functional and Structural Genomics: Functional genomic and proteomic approaches to disease resistance and susceptibility
• Genome Evolution: Evolution of disease resistance genes

Description: My current research program has been on understanding the molecular basis of host-pathogen interaction. The soybean-Phytophthora sojae interaction has been the main model system investigated extensively in our lab to understand the molecular basis of plant disease resistance. We are also investigating the soybean-Fusarium virguliformae interaction to understand the mechanism used by a phytotoxin to cause plant disease. In addressing the above biological questions we are applying both functional genomics and proteomics approaches that require bioinformatics tools.

Selected Publications:

• Narayanan, N.N ., Tasma, I.M., Grant, D., Shoemaker, R., and Bhattacharyya, M.K. (2008) Identification of candidate signaling genes including regulators of chromosome condensation 1 proteins family differentially expressed in the soybean-Phytopthora sojae interaction.Theoretical and Applied Genetics, in press.
• Tasma, I.M., Brendel, V., Whitham S.A., and Bhattacharyya, M.K. (2008) Expression and Evolution of the Phosphoinositide-specific Phospholipase C Gene Family in Arabidopsis thaliana. Plant Physiology and Biochemistry. 46:627-637.
• Gao, H., and Bhattacharyya M.K. (2008) The soybean-Phytophthora resistance locus Rps1-k encompasses coiled coil-nucleotide binding-leucine rich repeat-like genes and repetitive sequences. BMC Plant Biol. 8: 29.

• Ji, J., Scott, M.P., and Bhattacharyya, M.K. (2006) Light is essential for degradation of ribulose-1,5-biphosphate carboxylase-oxygenase large subunit during sudden death syndrome development in soybean. Plant Biology 8:597-605.

• Gao, H., Narayanan, N., Ellison, L., and Bhattacharyya M.K. (2005) Two classes of highly similar coiled coil-nucleotide binding-leucine rich repeat genes isolated from the Rps1-k locus encode Phytophthora resistance in soybean. Mol. Plant-Microbe Interact. 18: 1035-1045.

• Bhattacharyya, M.K. , Narayanan, N. N., Gao, H., Salimath, S.S., Santra, D., Ellison, L., Brar, H., Kasuga, T., Liu, Y., Espinosa, B., Marek, L.F., Shoemaker, R.C., Gijzen, M. and Buzzell, R.I. (2005) Identification of a large cluster of coiled coil-nucleotide binding site-leucine rich repeat-type genes from the Rps1 region containing Phytophthora resistance genes in soybean. Theor. Appl. Genet. 111:75 – 86.
   

Vita: Click here to download

Website: Madan Bhattacharyya

*Adam Bogdanove

Associate BCB Faculty Member

Education: Ph.D., Cornell, 1997

Research Interests: Genomic and proteomic approaches to bacterial plant diseases and plant disease resistance

• Functional and Structural Genomics-- Genomic and proteomic approaches to bacterial plant pathology and plant disease resistance mechanisms, including bacterial genomic sequence analysis and protein profiling, and plant microarray and mutational analyses
• Information Integration and Data Mining

Description:

Selected Publications:

• Meyer, D.F., and Bogdanove, A.J. (2008). Genomics-driven advances in Xanthomonas biology. In Plant Pathogenic Bacteria: Genomics and Molecular Biology, R.W. Jackson, ed. (Norwich, UK, Horizon Scientific Press), in press.
• Patil, P.B., Bogdanove, A.J., and Sonti, R.V. (2007) The role of horizontal transfer in the evolution of a highly variable lipopolysaccharide biosynthesis locus in xanthomonads that infect rice, citrus and crucifers. BMC Evol. Biol. 7:243.
• Wang, L. Makino, S., Subedee, A. and Bogdanove, A.J. (2007) Novel candidate virulence factors in rice pathogen Xanthomonas oryzae pv. oryzicola revealed by mutational analysis. Applied Env. Microbiol. 73:8023-8027.
• Nissinen, R.M, Ytterberg, A.J., Bogdanove, A.J., van Wijk, K.J., and Beer, S.V. (2007) Analyses of the secretomes of Erwinia amylovora and selected hrp mutants reveal novel type III secreted proteins and an effect of HrpJ on extracellular harpin levels. Molecular Plant Pathol. 8:55-67.
• Wise, R.P., Moscou, M.J., Bogdanove, A.J., and Whitham, S.A. (2007). Transcript profiling in host-pathogen interactions. Ann. Rev. Phytopathol. 45:329-369.
• Nino-Liu, D. O., Ronald, P. C., and Bogdanove, A. J. (2006) Xanthomonas oryzae pathovars: model pathogens of a model crop. Molecular Plant Pathol. 7:303-324.

*Volker Brendel

Education: Ph.D., Weizmann ( Israel), 1986

Research Interests: Gene identification, pre-mRNA splicing

Description: Plant genomics and molecular genetics

• Bioinformatics-- Algorithms for gene identification in genomic sequences; sequence alignment methods; plant transposon molecular biology; molecular phylogeny

Selected Publications:

• Duvick, J., Fu, A., Muppirala, U., Sabharval, M., Wilkerson, M.D., Lawrence, C.J., Lushbough, C. & Brendel, V. (2008) PlantGDB: a resource for comparative plant genomics. Nucl. Acids Res. 36, D959-D965.
• Dong, Q., Wilkerson, M.D. & Brendel, V. (2007) Tracembler - software for in silico chromosome walking in unassembled genomes. BMC Bioinformatics 8, 151.
• Schlueter, S.D., Wilkerson, M.D., Dong, Q. & Brendel, V. (2006) xGDB: open-source computational infrastructure for the integrated evaluation and analysis of genome features. Genome Biol. 7, R111.
• Wang, B.-B. & Brendel, V. (2006) Genome-wide comparative analysis of alternative splicing in plants. Proc. Natl. Acad. Sci. USA 103, 7175-7180.
• Wang, B.-B. & Brendel, V. (2006) Molecular characterization and phylogeny of U2AF1 homologs in plants. Plant Physiol. 140, 624-636.
• Gremme, G., Brendel, V., Sparks, M.E. & Kurtz, S. (2005) Engineering a software tool for gene structure prediction in higher organisms. Information Software Technol. 47, 965-978.
• Brendel, V. (2005) Novel tools for plant genome annotation and applications to Arabidopsis and rice. In J.P. Gustafson, R. Shoemaker & J.W. Snape (eds.), Genome Exploitation: Data Mining the Genome, Stadler Genetics Symposia Series, 23rd Symposium, Springer, NY, U.S.A.
• Sparks, M.E. & Brendel, V. (2005) Incorporation of splice site probability models for non-canonical introns improves gene structure prediction in plants. Bioinformatics 21, iii20-iii30.
• Dong, Q., Lawrence, C.J., Schlueter, S.D., Wilkerson, M.D., Kurtz, S., Lushbough, C. & Brendel, V. (2005) Comparative plant genomics resources at PlantGDB. Plant Physiol. 139, 610-618.
• Pan, X., Stein, L. & Brendel, V. (2005) SynBrowse: a synteny browser for comparative sequence analysis. Bioinformatics 21, 3461-3468.
• Lawrence, C.J., Seigfried, T.E. & Brendel, V. (2005) MaizeGDB - the community resource for access to diverse maize data. Plant Physiol. 138, 55-58.
• Dong, Q., Kroiss, L., Oakley, F.D., Wang, B.-B. & Brendel, V. (2005) Comparative EST analyses in plant systems. In Molecular Evolution: Producing the Biochemical Data, E.A. Zimmer and E.H. Roalson (eds.), Methods Enzymol. 395, 400-418.
• Brendel, V. (2005) Gene structure prediction in plant genomes. In M.J. Dunn, L.B. Jorde, P.F.R. Little and S. Subramaniam (eds.), Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics, Wiley & Sons, Chichester, UK. DOI: 10.1002/047001153X.g402303.
• Dong, Q. & Brendel, V. (2005) Computational identification of related proteins: BLAST, PSI-BLAST, and other tools. In J.M. Walker (ed.), The Proteomics Protocols Handbook, Humana Press, U.S.A., pp. 555-570.
• Schlueter, S.D., Wilkerson, M.D., Huala, E., Rhee, S.Y. & Brendel, V. (2005) Community-based gene structure annotation for the Arabidopsis thaliana genome. Trends Plant Sci. 10, 9-14.

Website: Volker Brendel

Anne Bronikowski

Associate BCB Faculty Member

Education: Ph.D., University of Chicago, 1997

Research Interests: Evolution of life history variation with an emphasis on the evolution of senescence

• Bioinformatics-- Our research focuses on the evolution of life history variation with an emphasis on the evolution of senescence (the functional decline in biochemical and physiological processes with age). We address fundamental questions in life history evolution using field studies, laboratory experiments (physiological and molecular), and mathematical modeling. Current research focuses on the evolution and ecology of senescence in 1) natural reptile populations; 2) laboratory populations of mice and 3) semi-natural populations of baboons
• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking—Same as above

Description: We address fundamental questions in life history evolution using field studies, laboratory experiments (physiological and molecular), and mathematical modeling

Selected Publications:

• Promislow, D.E.L. and Bronikowski, A.M. in press. The Evolutionary Genetics of Senescence. In Evolutionary Genetics: Concepts and Case Studies. Eds. J. Wolf and C. Fox. Oxford University Press, U.K.
• Bronikowski, A.M. and D.E.L. Promislow.   2005. Testing evolutionary theories of aging in wild populations. Trends in Ecology and Evolution 20(6): 271-273 .
• Gammie, S.C., Hasen, N.S., Awad, T.A., Auger, A.P., Jessen, H.M., Panksepp, J.B., and Bronikowski, A.M.  2005. Gene array profiling of large hypothalamic CNS regions in lactating and randomly cycling virgin mice. Molecular Brain Research 139: 201-211.
• Bronikowski, A.M., Carter, P.A., Morgan, T.J., Garland, T. Jr., Ung, N., Pugh, T.D., Weindruch, R. and Prolla, T.A. 2003. Lifelong voluntary exercise in the mouse prevents age-related alterations in gene expression in the heart. Physiological Genomics 12: 129–138.

Vita: Click here to download

Website: Anne Bronikowski

Steven Cannon

Associate BCB Faculty Member

Education: Ph.D., University of Minnesota, 2003

Research Interests: Plant genome and gene family evolution, comparative genomics, bioinformatic methods for gene and genome sequence analysis.

BCB Research Areas:

• Bioinformatics-- methods for gene and genome sequence analysis, including genome comparisons, phylogenetics, and high-throughput transcript profiling.
• Genome evolution-- patterns and rates of genome rearrangement; effects of polyploidy and transposon activity.

Description: I am a USDA-ARS Research Geneticist, and an adjunct assistant professor in the Agronomy Department.
My ARS research group focuses on bioinformatics for crop improvement, particularly in soybean and other crop legumes. We do this by developing software for analyzing and transferring information between crop and model species - including sequence, genetic, functional, and phenotype data. We study the evolution of disease resistance and nitrogen fixation, and the responses of genomes to polyploidy. We also provide support for two genome sequencing efforts: soybean, and a relative of alfalfa called Medicago truncatula. This support includes development of genetic markers, development of web-based tools for genomic data access and visualization.

Selected Publications:

• Ameline-Torregrosa C, Wang B-B, O’Bleness M, Deshpande,S, Zhu H, Roe BA, Young ND, Cannon SB (2008) Identification and Characterization of NBS-LRR Encoded Genes in the Model Plant Medicago truncatula Plant Physiology, 146:5-21.
• Zhang X-C, Wu X, Findley S, Wan J, Libault M, Nguyen HT, Cannon SB, Stacey G (2007) Characterization of plant LysM domains and molecular evolution and comparative genomics of plant LysM type receptor-like kinases. Plant Physiology 144:623-636.
• Cannon SB, Sterck L, Rombauts S, Sato S, Cheung F, Gouzy JP, Wang X, Mudge J, Vasdewani J, Scheix T, Spannagl M, Nicholson C, Humphray SJ, Schoof H, Mayer KFX, Rogers J, Quetier F, Oldroyd GE, Debelle F, Cook DR, Ernest F. Retzel, Roe BA, Town CD, Tabata S, Van de Peer Y, ND Young (2006) Legume genome evolution viewed through the Medicago truncatula and Lotus japonicus genomes. PNAS 103(40):14959-64.
• Mudge J, Cannon SB, Kalo P, Oldroyd GED, Roe BA, Town CD, Young ND (2005) Hypersyntenic Regions in the Genomes of Soybean, Medicago truncatula, and Arabidopsis thaliana. BMC Plant Biology, 2005.

Websites: http://soybase.org/ http://medicago.org/

Vita: Click here to download

Website: Steven Cannon

Hui-Hsien Chou

Education: Ph.D., University of Maryland at College Park, 1996

Research Interests: Bioinformatics, computational and molecular biology

Description: My research interest has been the development of sophisticated computer science algorithms for efficiently solving large scale biological research problems, e.g., the automatic DNA sequence clean up programs (LUCY1 & 2), an efficient whole-genome oligo microarray design tool (PICKY), and an automatic Perl programming tool (VECT) for biologists. My software tools employ novel approaches to computing and generally provide better results than previous methods. For example, while most microarray design tools are still based on the sequence level comparison to screen out nontargets, my PICKY program has embedded a complete suite of thermodynamic equations in its calculations to infer the best oligo candidates based on the whole genome, and it does so orders of magnitude faster than any other comparable microarray design tools with the same computation depth. My recent focus is on the whole-genome siRNA design using a similar thermodynamic calculation approach and to verify the designs in my molecular biology lab using C. elegans as the model.
 
Ongoing projects: National Institute of General Medical Sciences, Visual Data Extraction and Conversion Programming Tool - The goal of this project is to develop an auto-programming tool for biomedical scientists to help them handle the large amount of data in their research; National Science Foundation Plant Genome Research Program - A Rice Oligonucleotide Array - Rice has become a model for grasses and cereal because of its small genome size, available genome sequence, and ease of transformation. The structural and functional analysis of rice genes has broad practical implications for the other economically important cereals such as corn and wheat. This project will design, manufacture and distribute whole genome rice microarrays to the public.

Selected Publications:

• Young-Su Seo, Malinee Sriariyanun, Li Wang, Janice Pfeiff, Jirapa Phetsom, Ye Lin, Ki-Hong
  Jung, Hui-Hsien Chou, Adam J Bogdanove and Pamela C Ronald. A two-genome
  microarray for the rice pathogens Xanthomonas oryzae pv. oryzae and X. oryzae pv. oryzicola
  and its use in the discovery of a difference in their regulation of hrp genes. BMC
  Microbiology, 8(1):99, 2008.
• Scott Emrich, Li Li, Tsui-Jung Wen, Marna Yandeau-Nelson, Yan Fu, Ling Guo, Hui-Hsien
  Chou, Srinivas Aluru, Daniel Ashlock, and Patrick Schnable. Nearly identical paralogs
  (NIPs): implications for maize (Zea mays L.) genome evolution. Genetics, 175(1): 429–439, 2007.
• Philip M. Maher, Hui-Hsien Chou, Elizabeth Hahn, Tsui-Jung Wen, and Patrick S. Schnable. GRAMA:  Genetic Mapping Analysis of Temperature Gradient Capillary Electrophoresis (TGCE) Data. Theoretical and Applied Genetics, 113(1):156162, 2006.
• Hui-Hsien Chou. Vect: an automatic visual Perl programming tool for nonprogrammers. BioTechniques, 38:615621, April 2005.
• Song Li and Hui-Hsien Chou. UBViz: Explore Biochemical Pathways in 3-D Space. BioTechniques, 38:540542, April 2005.
• Hui-Hsien Chou, An-Ping Hsia, Denise L. Mooney, and Patrick S. Schnable. Picky: Oligo Microarray Design for Large Genomes. Bioinformatics, 20:28932902, Nov. 2004.
• Song Li and Hui-Hsien Chou. Lucy2: an interactive DNA sequence quality trimming and vector removal tool. Bioinformatics, 20:28652866, Nov. 2004.

Department Website: Hui-Hsien Chou

*Dianne Cook

Education: Ph.D., Rutgers, 1993

Research Interests: Visualization of high-dimensional data, linking data views with other visualization of biological phenomenon

• Bioinformatics-- Visualization of multivariate, high-dimensional data, in particular gene expression data, and metabolic networks. Interested developing methods for linking data views with other informative visualization of biological phenomenon
• Mathematical Biology, Computational Modeling, Metabolic and Developmental Networking—Same as above

Description: My research is in methods for visualizing high-dimensional data using interactive and dynamic methods. This includes data arising from biological experiments such as microarray data, metabolomics and proteomics. We're developing software to assist in this, called GeneGobi, which builds functionality in the data analysis language R and the data visualization software GeneGobi

Selected Publications:

• Hobbs , J., Wickham, H., Hofmann, H. and Cook, D. (2008) Glaciers Melt as Mountains Warm: A Graphical Case Study Computational Statistics, To appear.
• Lawrence, M., Cook, D., Lee, E.-K., Babka, H. and Wurtele, E. (2008) explorase: Multivariate Exploratory Analysis and Visualization for Systems Biology, Journal of Statistical Software, 25(9):http://www.jstatsoft.org/v25/i09.
• Cook, D., Hofmann, H., Lee, E.-K., Yang, H., Nikolau, B., and Wurtele, E. (2007) Exploring Gene Expression Data, Using Plots, Journal of Data Science, 5(2):151{182.
• Lee, E.-K., Cook, D., Klinke, S., and Lumley, T. (2005). Projection Pursuit for Exploratory Supervised Classification. Journal of Computational and Graphical Statistics, bf 14(4):831{846.
• Swayne, D. F., Temple Lang, D., Buja, A. and Cook, D. (2003) GGobi: Evolving from XGobi into an Extensible Framework for Interactive Data Visualization, Journal of Computational Statistics and Data Analysis, 43(4):423{444.
• Wurtele, E., Li, J., Diao, L., Zhang, H., Foster, C., Fatland, B., Dickerson, J., Brown, A., Cox, Z., Cook, D., Lee, E. K., Hofmann, H. (2003) MetNet: Software to Build and Model the Biogenetic Lattice of Arabidopsis, Comparative and Functional Genomics, 4:239{245.

Link: http://www.public.iastate.edu/~dicook/GeneGobi/MetNet_GeneGobi.htm

Vita: Click here to download

Website: Dianne Cook

Jack Dekkers

Education: Ph.D., Wisconsin, Madison, 1989

Research Interests: Integrating molecular and quantitative genetics for animal breeding programs

• Biological statistics -- Statistical methods for QTL detection and for estimating relationships between QTL and phenotype; identifying genes of economic importance in swine and poultry; systems analysis approaches to optimize the use of molecular genetic information in genetic improvement programs.

Description: Quantitative genetics and animal breeding with application to swine and poultry genetics, including design and optimization of breeding strategies, use of molecular genetic information, QTL detection, and economic aspects of breeding programs.

Selected Publications:

• Li, Y., H.N. Kadarmideen, and J.C.M. Dekkers. 2008. Selection on Multiple QTL with Control of Gene Diversity and Inbreeding for Long-term Benefit. J. Anim. Breed. Genet. (Accepted)
• Pyiasatian, N., R.L. Fernando, and J.C.M. Dekkers. 2008. Introgressing multiple QTL in breeding programs of limited size. J. Animal Breeding Genetics (In Press)
• Dekkers , J.C.M., and J.H.J. van der Werf. 2007. Strategies, limitations, and opportunities for marker-assisted selection in livestock. In: E. Guimaraes, J. Ruane, B. Scherf, A. Sonnino, and J. Dargie (Eds): Marker-Assisted Selection. Current status and future perspectives in crops, livestock, forestry and fish: Current Status and the Way Forward. FAO, Rome, Italy.
• Andreescu, C., S. Avendano, S. Brown, A. Hassen, S.J. Lamont, and J.C.M. Dekkers. 2007. Linkage disequilibrium in related breeding lines of chickens. Genetics 177: 2161–2169
• Habier, D., R.L. Fernando, J.C.M. Dekkers. 2007. The impact of relationship information genome-assisted breeding values. Genetics 177: 2389–2397
• Heifetz, E.M., J.E. Fulton, N.P. O'Sullivan, J.A. Arthur, J. Wang, J.C.M. Dekkers, and M. Soller. 2007. Mapping quantitative trait loci affecting susceptibility to Marek's disease virus in a backcross population of layer chickens. Genetics 177: 2417–2431.
• Dekkers , J.C.M. 2007. Prediction of response to marker-assisted and genomic selection using selection index theory. J. Anim. Breed. Genet. 124: 331-341
• Wang, J., K. Koehler, and J.C.M. Dekkers. 2007. Interval mapping of quantitative trait loci with selective DNA pooling data. Genetics Selection Evolution 39: 685-709.

Vita: Click here to download

Website: Jack Dekkers

*Julie Dickerson

Education: Ph.D., USC, 1993

Research Interests: Fuzzy expert systems, metabolic networks, macromolecular structure-function relationships. Systems biology and modeling of metabolic networks, analysis of microarray and
metabolomic data using pattern recognition methods, and data visualization in virtual reality

• Bioinformatics--Systems biology and modeling of metabolic networks, analysis of microarray and metabolomic data using pattern recognition methods, and data visualization in virtual reality
• Macromolecular Structure and Function-- Same as above

Description:

Selected Publications:

• S.Y. Rhee, J.A. Dickerson, D. Xu, “ Bioinformatics and Its Applications in Plant Biology,” Annual Review of Plant Biology, 57, 335-359, 2006.
• Y. Yang, L. Engin, E.S. Wurtele, Carolina Cruz-Neira, J.A. Dickerson, “Integration of metabolic networks and gene expression in virtual reality,” Bioinformatics, 21 : 3645-3650 2005.
• L. Shen, J. Gong, R. A. Caldo, D. Nettleton, D. Cook, R.P. Wise, J. A. Dickerson, “Barleybase – An Expression Profiling Database For Plant Genomics,” Nucleic Acids Research , 33 (suppl_1): D614-618, 2004 .
• P. Du, J. Gong, Eve S. Wurtele, and Julie A. Dickerson, “Modeling Gene Expression Networks using Fuzzy Logic,” Special issue of IEEE Transactions on Systems, Man and Cybernetics, Part B,35(6):1351-1359, 2005.
• E. S. Wurtele, J. Li, L. Diao, H. Zhang, C. Foster, B. Fatland, J. A. Dickerson, A. Brown, Z. Cox, D. Cook, E.-K. Lee, and H. Hofmann, “MetNet: software to build and model the biogenetic lattice of Arabidopsis,” Comparative and Functional Genomics, 4, 239-245, 2003.

Vita: Click here to download

Website: Julie Dickerson

Associate BCB Faculty Member

Education: Ph.D., Cornell, 1986

Research Interests: Modeling virus sequence evolution and immune system response, ecological and environmental statistics

• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking-- Modeling virus sequence evolution and immune system response, ecological and environmental statistics

Description: develops and evaluates statistical methods to answer interesting biological questions.  A lot of this work is collaborative.  The themes are using likelihood inference in non-standard situations and using computer-intensive methods

Selected Publications:

• Schleuter, J.A., Dixon, P., Granger, C., Grant, D., Clark, L., Doyle, J.J., and Shoemaker, R.C. 2004. Mining EST databases to resolve evolutionary events in major crop species. Genome 47:868-876
• Picasso, V.D., Brummer, E.C., Liebman, M., Dixon, P.M. and Wilsey, B.J. 2008. Crop species diversity affects productivity and weed suppression in perennial polycultures under two management strategies. Crop Science 48:331-342.
  Prasifka, J.R., Hellmich, R.L. Dively, G.P., Higgins, L.S., Dixon, P.M., and Duan, J.J. 2008. Selection of nontarget arthropod taxa for field research on transgenic insecticidal crops: using empirical data and statistical power. Environmental Entomology 37:1-10
  Schmidt, N.P., O’Neal, M.E., and Dixon, P.M. 2008. Aphidophagous predators in Iowa soybean: a community comparison across multiple years and sampling methods. Annals Ent. Soc. Amer. 101:341-350.
  Xu, Z., Gleason, M.L, Mueller, D.S., Esker, P.D., Bradley, C.A., Buck, J.W., Dixon, P.M., and Monteiro, J.E.B.A. 2008. Overwintering of Sclerotium rolfsii and S. rolfsii var. delphinii in different latitudes of the United States. Plant Disease 92:719-724.
  Esker, P.D, Gibb KS, and Dixon, P.M., Survival Analysis and Space-Time Point Pattern Analysis to Improve the Epidemiological Understanding of the Papaya-Papaya Yellow Crinkle Pathosystem. Plant Health Progress, in press.
  Scott, E.M. and Dixon, P.M. Statistical Sampling Designs for Radionuclides. book chapter, in review
  Westerrnan, P.R., Dixon, P.M., and Liebman, M. Burial rates of surrogate seeds in arable fields. Weed Research, submitted.

Vita: Click here to download

Website: Philip Dixon

*Drena Dobbs

Education: Ph.D. Oregon, 1983

Research Interests: Computational biology; predicting protein and nucleic acid structure, function, and interactions

• Macromolecular Structure and Function-- Analysis and prediction of macromolecular structure and function; protein-protein, protein-nucleic acid interactions, determinants of molecular recognition.

Description: Long-term research goals of the Dobbs group are to understand how proteins and nucleic acids achieve their functional three-dimensional structures and to elucidate mechanisms that determine recognition and regulate interactions among proteins, nucleic acids and other molecules in cells.  We use both computational and wet-lab experimental approaches to explore the structure and function of important macromolecular complexes, in close collaboration with several groups at Iowa State, University of Minnesota, and Harvard University.

Current areas of focus include: development of novel antiviral therapies against HIV-1 and other lentiviruses; rational design of zinc finger proteins (ZFPs) as tools for genomic modification and gene therapy; prediction of epitopes and nucleic acid binding residues in proteins; and prediction and experimental validation of structural and functional effects of mutations and SNPs in proteins. For details, please visit the Dobbs Lab website: http://ddobbs.public.iastate.edu/.

Selected Publications:

• Ihm, Y., Sparks, W.O., Lee, J.H., Cao, H., Culver, G., Carpenter, S., Wang, C.Z., Ho, K.M., Dobbs, D. (2009) Structural model of the Rev regulatory protein from equine infectious anemia virus. PLoS ONE 3:e4178.
• Sander, J.D., Zaback, P., Joung, J.K., Voytas, D.F., Dobbs, D. (2009) An affinity-based scoring scheme for predicting DNA-binding activities of modularly assembled zinc-finger proteins. Nucleic Acids Res. 37:506-515.
• Fu, F., Sander, J.D., Maeder, M., Thibodeau-Beganny, S., Joung, J.K., Dobbs, D., Miller, L., Voytas, D.F. (2009) Zinc Finger Database (ZiFDB): a repository for information on C2H2 zinc fingers and engineered zinc-finger arrays. Nucleic Acids Res 37:D279-283.
• Lee, J.-H., Culver, G., Carpenter, S., Dobbs, D. (2008). Analysis of the EIAV Rev-responsive element (RRE) reveals a conserved RNA motif required for high affinity Rev binding in both HIV-1 and EIAV. PLoS ONE 3:e2272.
• El-Manzalawy, Y., Dobbs., Honavar, V. (2008) On evaluating MHC-II binding peptide prediction methods. PLoS ONE 3:e3268.
• Yan, C., Wu, F., Jernigan, R., Dobbs, D., Honavar, V. (2008) Characterization of protein-protein interfaces. Protein J. 27:59-70.
• Dunn-Thomas, T., Dobbs, D.L., Sakaguchi, D., Young, M.J., Honavar, V., Greenlee, H.M.W. (2008), Proteomic differentiation between murine retinal and brain derived progenitor cells. Stem Cells Dev. 17: 119-132.
• Lee, J.-H., Culver, G., Carpenter, S., Dobbs, D. (2008). Analysis of the EIAV Rev-responsive element (RRE) reveals a conserved RNA motif required for high affinity Rev binding in both HIV-1 and EIAV. PLoS ONE 3:e2272.
• Maeder, ML., Thibodea-Beganny, S., Osiak, A., Wright, DA., Anthony, RM., Eichtinger, M., Jiang, T., Foley, JE., Winfrey, RJ., Townsend, JA., Unger-Wallace, E., Sander, JD., Dobbs, D., Cathomen, T., Voytas, DF., Joung, JK. ( 2008) Efficient gene modification enabled by an OPEN (Oligomerized Pool ENgineering) platform for constructing zinc finger nucleases. Mol. Cell. 31:294-301.
• EL-Manzalawy, Y., Dobbs, D., Honavar, V. (2008) Predicting linear B-cell epitopes using string kernels . J. Mol. Recognit . 21:243-255.
• EL-Manzalawy, Y., Dobbs, D., Honavar, V. (2008) Predicting protective linear B -cell epitopes using evolutionary information IEEE Int. Conf. Bioinf. Biomed. (BIBM 2008), pp. 289-292.
• Lee, J.-H., Hamilton, M., Gleeson, C., Caragea, C., Zaback, P., Sander, J.D., Li, X., Wu, F., Terribilini, M., Honavar, V., Dobbs, D. (2008). Striking similarities in structure and nucleic acid binding sites of diverse telomerase proteins revealed by combining structure prediction and machine learning approaches. Pac. Symp. Biocomput. (PSB 2008) 13:501-512.
• Towfic, F., Caragea, C., Dobbs, D., Honavar, V. (2008). Struct-NB: Predicting protein-RNA binding sites using structural features . Int. J. Data Min Bioinform. (In press).
• Caragea, C., Sinapov, J., Dobbs, D., Honavar, V. (2008) Using global sequence similarity to enhance biological sequence labeling. IEEE Int. Conf. IEEE Int. Conf. Bioinf. Biomed. (BIBM 2008) pp. 104-111.

Vita: Click here to download

Website: Drena Dobbs

*Karin Dorman

Education: Ph.D., UCLA, 2001

Research Interests: Mathematical modeling, virus evolution, phylogenetics

• Genome Evolution-- I employ mathematical models and computational tools to capture the essential aspects of biological systems. I am interested in the role of pathogen diversity in diseases caused by rapidly evolving organisms (HIV-1, EIAV, HCV), statistical techniques for the detection of recombination or gene conversion, and stochastic models for explaining the uncertainty in biological outcomes
• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking-- Same as above

Description: I am interested in the genomic changes occurring in fast-evolving viruses and how these changes can be used to better understand how they cause disease. I have developed methods to detect recombination and selection in the hundreds and thousands of genomic sequences available for viruses like HIV, HBV, and EIAV. I am currently developing new methods to detect and quantitate selection in overlapping reading frames, a genomic structure common in viruses and heretofor largely unstudied. I am also developing computational models of virus/host interactions and the accompanying statistical methods for data analysis and  tting. In the future, I will continue to develop new methods for genetic analysis, for example a model to estimate transposon birth and death rates, and explore extended models of host/pathogen interactions, for example to test the hypothesis that changes in EIAV during disease are helping the virus evade a maturing immune response.

Selected Publications:

• J. A. Farfan-Ale, M. A. Loro~no-Pino, J. E. Garcia-Rejon, E. Hovav, A. M. Powers, M. Lin, K. S. Dorman, K. B. Platt, L. C. Bartholomay, V. Soto, B. J. Beaty, R. S. Lanciotti, B. J. Blitvich. (2008) Detection of RNA from a novel West Nile-like virus and high prevalence of an insect-specific avivirus in mosquitoes in the Yucatan Peninsula of Mexico. American Journal of Tropical Medicine & Hygiene. Accepted.
• E. W. Bloomquist, K. S. Dorman, M. A. Suchard (2008) StepBrothers: inferring spatially shared ancestries among recombinant viral sequences. Biostatistics. In press.
• G. M. Dancik, K. S. Dorman (2008) mlegp: statistical analysis for computer models of biological systems using R. Bioinformatics. Accepted.
• B. Su, W. Zhou, K. S. Dorman, D. E. Jones. (2008) Mathematical modeling of immune response in tissues. Computational and Mathematical Methods in Medicine. Accepted.
• W. O. Sparks, K. S. Dorman, S. Liu, S. Carpenter. (2008) Selection on Rev during persistent equine infectious anemia virus infection. Journal of General Virology. 89:1043-1048.
• M. L. Rajaram, V. N. Minin, M. A. Suchard, K. S. Dorman. (2007) Hot and Cold: Spatial Fluctuation in HIV-1 Recombination Rates. Proceedings of the IEEE 7th Con- ference on Bioinformatics and Bioengineering (BIBE2007).
• M. E. Sparks, V. Brendel, K. S. Dorman. (2007) Markov model variants for appraisal of coding potential in plant DNA. Lecture Notes in Computer Science. 4463:394{405.
• V. N. Minin, K. S. Dorman, F. Fang, M. A. Suchard. (2007) Spatially smoothing change-point processes for phylogenetic mapping of recombination hot-spots. Genetics. 175(4):1773{1785.
• F. Fang, J. Ding, V. N. Minin, M. A. Suchard, K. S. Dorman. (2007) cBrother: Relaxing parental tree assumptions for Bayesian recombination detection. Bioinfor- matics. 23(4):507{508.
• K. S. Dorman. (2007) Identifying dramatic selection shifts in phylogenetic trees. BMC Evolutionary Biology. 7(suppl. 1):S10.

Vita: Click here to download

Website: Karin Dorman

Oliver Eulenstein

Education: Ph.D., Bonn, 1998

Research Interests: Design and analysis of algorithms for molecular biology

• Bioinformatics-- Design and analysis of algorithms in computational biology: phylogenetic trees, protein folding, physical mapping, genome rearrangements, sequence alignment, fragment assembly
• Genome Evolution-- Same as above

Description: Development of algorithms to solve problems in molecular biology

Selected Publications:

• M. J. Sanderson, A. C. Driskell, R. H. Ree, O. Eulenstein, and S. Langley Obtaining Maximal Concatenated Phylogenetic Data Sets from Large Sequence Databases. Mol Biol Evol 20: 1036-1042 (2003).
• Y. P. Yuan, O. Eulenstein, M. Vingron and P. Bork, Towards detection of orthologues in sequence databases Bioinformatics, 285-289, 14,3 (1998).
• O. Eulenstein, B. Mirkin and M. Vingron, Duplication-Based Measures of Difference Between Gene- and Species Trees Journal of Computational Biology, 135--148, 5 (1998).

Vita: Click here to download

Website: Oliver Eulenstein

Rohan Fernando

Education: Ph.D., Illinois, Urbana-Champaign, 1984

Research Interests: Methods for mapping QTL and for marker-assisted selection

• Functional and Structural Genomics-- Mapping and characterizing quantitative trait loci; use of genetic data in animal breeding

Description: Statistical methodology for mapping QTL; marker assisted selection; and genetic evaluation and parameter estimation in crossbred populations

Selected Publications:

• Gianola, D., R. L. Fernando, and A. Stella. 2006. Genomic assisted prediction of genetic value with semi-parametric procedures. Genetics 173:1761-1776.
• Minick, J.A., L. R. Totir, D. E. Wilson, R. L. Fernando. 2006. Conception rate in Angus heifers. J. Anim. Sci. 84:2022-2025.
• Abraham, K. J., L. R. Totir, and R. L. Fernando. 2007. Improved techniques for sampling complex pedigrees with the Gibbs sampler. GSE 39: 27-38.
• Zhao, H.H., R.L. Fernando, and J.C.M. Dekkers. 2007. Power and precision of alternate methods for linkage disequilibrium mapping of QTL. Genetics 175: 1975-1986
• Habier, D., R.L. Feranndo And J.C.M. Dekkers. 2007. The Impact of genetic relationship information on genome-assisted breeding values. Genetics 177:2389-3397.
• Fernando, R.L., D. Habier, C. Stricker, J.C.M. Dekkers, and L.R. Totir. 2007. Genomic selection. Acta Agricultrae Scandinavica, Section A, 57:192-195.
• Fernando, R. L. Mapping QTL in Outbred Populations. In Biotechnology and Quantitative Genetics.
• Pita, F. V. C., R. L. Fernando, L. R. Totir, M. Schelling, C. Stricker, S. A. Fernandez, J. C. M. Dekkers, P. S. Lopes. A comparison of public domain programs for computing identity by descent coefficients. Genetics Selection and Evolution.
• Pita, F. V. C., R. L. Fernando, L. R. Totir, P. S. Lopes. An improved approximation of the gametic covariance matrix for marker assisted genetic evaluation by BLUP. Genetic Selection and Evolution.
• Santos, N. T., A. E. Freeman, R. L. Fernando, J. C. M. Dekkers. Estimation of Adjustment Factors for Three Times a Day Milking Using a Random Regression Model. J. Dairy. Sci.
• Totir, L. R., R. L. Fernando, and K. J. Abraham. An efficient algorithm to compute marginal posterior genotype probabilities for every member of a pedigree with loops. Genetics.

Vita: Click here to download

Website: Rohan Fernando

*M. H. West Greenlee

Education: Ph.D., Iowa State, 1999

Research Interests: The molecular basis of neural differentiation

Description:

Selected Publications:

• Laura A. Hecker, Tim C. Alcon, Vasant G. Honavar, M. H. West Greenlee (2008) Using a seed-network to query large scale gene expression data from the developing retina. Bioinformatics and Biology Insights, 2008:2 91-102.
• Samantha Van Hoffelen, M. Heather W Greenlee, Matthew M Harper, Daniel T Au. (2008) Cell birth and death in the developing retina of the Brazilian opossum, Monodelphis domestica. Brain Res. 1195:28-42
• Tyra Dunn-Thomas, Drena L. Dobbs, Donald S. Sakaguchi, Michael J. Young, Vasant G. Honavar, M. Heather West Greenlee. (2008) Proteomic differentiation between murine retinal and brain derived progenitor cells. Stem Cells and Development, Jan 22 [Epub ahead of print]
• J. Smith, J. Greenlee, A. Hamir, and M. H. West Greenlee (2008) Retinal cell types are differentially affected in sheep with scrapie. Comparative Pathology: 138:12-22.
• J. Eucher, E. Uemura, D. Sakaguchi, M. H. West Greenlee (2006) Amyloid-beta peptide affects viability but not differentiation of embryonic and adult rat hippocampal progenitor cells. J. Exp. Neurol. 203:486-92

Vita: Click here to download

Website: M. Heather West Greenlee

*Xun Gu

Education: Ph.D., Texas, Houston, 1996

Research Interests: Computational biology, molecular evolution, comparative genomics

• Genome Evolution-- Computational molecular biology; molecular evolution; comparative genomics

Description:

Selected Publications:

• H Zhou, J Gu, S J. Lamont, Gu X * (2006) Evolutionary analysis for functional divergence of Toll-like receptor gene family and altered functional constraints. Journal of Molecular Evolution (in press)

• Leebens-Mack, J, Vision T, Brenner E,…Gu X … (2006) Taking the first steps towards a standard for reporting on phylogenies: Minimal Information About a Phylogenetic Analysis (MIAPA). OMIC Integrated Biology (in press).

• Guo, H, Weiss R. E., Gu, X, and Suchard, M. A. (2006) Time Squared: Repeated Measures on Phylogenies. Molecular Biology and Evolution (in press).

• Gu X. (2006) A Simple Statistical Method for Estimating Type-II (Cluster-Specific) Functional Divergence of Protein Sequences. Mol Biol Evol. Jul 24; [Epub ahead of print]

• Lin H, Zhu W, Silva JC, Gu X, Buell CR. (2006) Intron gain and loss in segmentally duplicated genes in rice. Genome Biol. 7(5):R41.

• Su Z, Wang J, Yu J, Huang X and Gu X*(2006) Evolution of Alternative Splicing after Gene Duplications. Genome Res. 16(2):182-9.

• Wu Q, Gu X, Wang Y, Li N, Liu X, Wu C, Yu L, Gu X. (2006) Neurotransmitter inactivation is important for the origin of nerve system in animal early evolution: a suggestion from genomic comparison. Prog Neurobiol. 78(6):390-5.

Vita: Click here to download

Website: Xun Gu

Kai-Ming Ho

Education: Ph.D., Berkeley, 1978

Research Interests: Protein structure and dynamics, membranes.

Selected Publications:

• H. B. Cao, Y. Ihm, C. Z. Wang, J. R. Morris, M. Su, D. Dobbs, and K. M. Ho. Three-dimensional
  threading approach to protein structure recognition, Polymer 45:687 (2004).
• W. C. Lu, C. Z. Wang, and K. M. Ho, "Effect of Chain Connectivity on the Structure of Lennard-Jones Liquid and Its Implication on Statistical Potentials for Protein Folding",Phys. Rev. E 69, 061920 (2004).
• D. M. Deaven and K. M. Ho. Molecular geometry optimization with a genetic algorithm, Phys. Rev. Lett. 75:288 (1995).
• H. B. Cao, C. Z. Wang, D. Dobbs, Y. Ihm, and K. M. Ho " Codability criterion for picking proteinlike
  structures from random three-dimensional configurations", Phys. Rev. E 74, 031921 (2006).
• W. C. Lu, C. Z. Wang, E. W. Yu, and K. M .Ho Dynamics of the trimeric AcrB transporter protein
  inferred from B-factor analysis of the crystal structure, Proteins 62, 152 (2006).
• T. Z. Sen, A. Kloczkowski, R. L. Jernigan, C. H. Yan, V. Honavar, K. M. Ho, C. Z. Wang, Y. Ihm, H. B. Cao, X. Gu, and D. Dobbs Predicting binding sites of hydrolase-inhibitor complexes by combining several
  methods, BMC Bioinformatics 5, 205 (2004).
• H. B. Cao, C. Z. Wang, and K. M. Ho Fast method for estimating the energy distribution of globular states
  of proteins", Phys. Rev. E 72, 021907 (2005).
• Y. Ihm, W. O. Sparks, J.-H. Lee, H. B. Cao, C. Z. Wang, S. Carpenter, K. M. Ho, and D. Dobbs,
  Structural Model of the Rev Regulatory Protein from Equine Infectious Anemia Virus (EIAV) submitted.

Vita: Click here to download

Website: Kai-Ming Ho

*Vasant Honavar

Education: Ph.D., Wisconsin, Madison, 1990

Research Interests: Bioinformatics and computational systems biology, artificial intelligence, computational systems biology, data mining and machine learning, databases and knowledge bases, information integration, semantic web, e-science

• Bioinformatics--Ontology-driven and probabilistic approaches to integrative and collaborative analysis of disparate biological data sets; description logics, ontology design, ontology tools, semantic web for life sciences including semantics based data integration, web services.
• Macromolecular Structure and Function--Data-driven discovery of macromolecular sequence-structure-function-interaction-expression relationships, identification of sequence and structural correlates of protein-protein , protein-RNA, and protein-DNA interactions, protein sub-cellular localization, automated protein structure and function annotation
• Computational Systems Biology-Qualitative, probabilistic, and dynamic modeling, simulation, and inference of protein-protein interaction networks, genetic regulatory networks, signal transduction networks and metabolic pathways; Biological Computation Evolutionary, Cellular and Neural Computation.
• Data Mining and Machine Learning- Statistical, information theoretic, linguistic and structural approaches to machine learning, Learning and refinement of Bayesian networks, causal networks, Markov networks and Markov random fields, decision networks, neural networks, support vector machines, kernel classifiers, multi-relational models, language models (n-grams, grammars, automata), Learning classifiers from sequential and spatial data; Learning relationships from multi-modal data (e.g., text, images), Learning classifiers from distributed data, multi-relational data, and semantically heterogeneous data; Incremental learning, Ensemble methods, multi-agent learning, spectral clustering, selected topics in computational learning theory.
• Semantic Web for e-science: Ontology-based user and query-centric approaches to information integration and acquisition of sufficient statistics for learning from data under different access and resource constraints from heterogeneous, distributed, autonomous, ubiquitous information sources, sensor networks, peer-to peer networks; description logics, ontology design, ontology tools, ontology-extended information sources, ontology-extended workflow components, ontology-extended agents and services, web service composition.

Description: My research interests cut across Computer Science, Information Science, Statistics, Cognitive Science, and Biological Sciences. This research is driven by fundamental scientific questions or important practical problems such as the following:

• How can we query and use information from autonomous, heterogeneous, distributed, autonomous data and knowledge sources?
• How can we build useful predictive models from large, distributed, semantically heterogeneous, autonomous data sources?
• How can we develop software environments for collaborative development, sharing, and use of large, complex, knowledge bases?
• How can we develop sophisticated machine learning algorithms for knowledge acquisition from richly structured data (sequences, images, graphs, text, etc.)
• How can we support the design, assembly and execution of complex web services using autonomously developed components?
• How can we represent and manipulate scientific knowledge in a form that lends itself to automated processing by the computer and at the same time, is comprehensible by, and communicable to humans?
• How can we develop information processing models of perception, learning, inter-agent communication, multi-agent interaction, coordination, and organization?
• How is information encoded, stored, retrieved, decoded, and used in macromolecular, neural, and cognitive systems?
• How can we discover the relationships between macromolecular sequence, structure, expression, interaction and macromolecular function?
• How can we construct accurate predictive models of signaling networks involved in cellular development, differentiation, and biological function?
• How can we model complex systems at multiple levels of abstraction in space and time?
• How can we automate scientific discovery?

Selected Publications:

• 1. Bao, J., Voutsadakis, G., Slutzki, G., and Honavar, V. (2008). On the Decidability of Role Mappings between Modular Ontologies. Proceedings of the 23nd Conference on Artificial Intelligence (AAAI-2008), AAAI, 404-409.
• 2. Caragea, C. and Honavar, V. (2008). Machine Learning in Computational Biology. In: Encyclopedia of Database Systems. Raschid, L. (ed). Springer. To appear.
• 3. Caragea, D. and Honavar, V. (2008). Learning Classifiers from Distributed Data. In: Encyclopedia of Database Technologies and Applications, Ferraggine, V.E., Doorn, J.H., and Rivero, L.C. (Ed). New York: Idea Group. In press.
• 4. Caragea, D. and Honavar, V. (2008). Learning Classifiers from Semantically Heterogeneous Data. In: Encyclopedia of Data Warehousing and Mining. Wang, J. (Ed). In press.
• 5. Dunn-Thomas, T., Dobbs, D.L., Sakaguchi, D. Young, M.J. Honavar, V. Greenlee, H. M. W. (2008). Proteomic Differentiation Between Murine Retinal and Brain Derived Progenitor Cells. Stem Cells and Development. 17: 191-131.
• 6. El-Manzalawy, Y., Dobbs, D., and Honavar, V. (2008). Predicting linear B-cell epitopes using string kernels. Journal of Molecular Recognition, DOI:10.1002/jmr.893
• 7. El-Manzalawy, Y., Dobbs, D., and Honavar, V. (2008). Predicting Flexible Length Linear B-cell Epitopes, 7th International Conference on Computational Systems Bioinformatics, Stanford, CA. Singapore: World Scientific. In press.
• 8. Hecker, L., Alcon, T., Honavar, V., and Greenlee, H. (2008). Analysis and Interpretation of Large-Scale Gene Expression Data Sets Using a Seed Network. Journal of Bioinformatics and Biology Insights. Vol. 2. pp. 91-102.
• 9. Honavar, V. and Caragea, D. (2008). Towards a Semantics-Enabled Infrastructure for Knowledge Acquisition from Distributed Data. In: Next Generation Data Mining. Kargupta, H. et. al., CRC Press. In press.
• 10. Hughes, L., Bao. J., Honavar, V., and Reecy, J. (2008). Animal Trait Ontology (ATO): the importance and usefulness of a unified trait vocabulary for animal species. Journal of Animal Science. In press.

Vita: Click here to download

Website: Vasant Honavar

*Richard Honzatko

Associate Faculty Member

Education: Ph.D., Harvard, 1982

Research Interests: Structure-function studies of proteins, X-ray diffraction

• Macromolecular Structure and Function--Structure-function studies of proteins by X-ray diffraction and biochemical techniques

Description: Structure determination of macromolecules of biological interest, crystallization of proteins and x-ray crystallography, energy-conformation analysis of protein ligand interactions

Selected Publications:

• Skaff, D.A., Kim, C.S., Tsai, H.J., Honzatko, R.B. and Fromm, H.J. (2005) Glucose 6-phosphate release of wild-type and mutant human brain hexokinases from mitochondria. J. Biol. Chem. 280,38403-38409.
• Iancu, C.V., Mukund, S., Fromm, H.J. and Honzatko, R.B. (2005) R-state AMP complex reveals initial steps of the quaternary transition of fructose-1,6-bisphosphatase. J. Biol. Chem. 280, 19737-19745.

Vita: Click here to download

Website: Richard Honzatko

Xiaoqiu Huang

Education: Ph.D., Penn State, 1990

Research Interests: Computational problems in genome sequencing and analysis

• Bioinformatics-- Computational problems in genome sequencing and analysis

Description: Assembly of DNA fragments into longer sequences, identification of genes in genomic DNA sequences, comparison of genomic DNA sequences.Xiaoqiu Huang is an associate professor in computer science at Iowa State University. He received his Ph.D. in computer science from Pennsylvania State University in 1990. Xiaoqiu Huang is interested in computational problems in genome sequencing and analysis. He is the author of a widely used CAP3 assembly program. He and his colleagues have recently developed a whole-genome assembly program named PCAP. PCAP has been used by Washington University Genome Center in chimpanzee and chicken genome projects.

Selected Publications:

• Huang, X. and Madan, A. (1999) CAP3: A DNA Sequence Assembly Program, Genome Research, 9: 868-877.
• Huang, X., Wang, J., Aluru, S., Yang, S.-P. and Hillier, L. (2003) PCAP: A Whole Genome Assembly Program, Genome Research, 13: 2164-2170.
• Huang, X. and Chao, K.-M. (2003) A Generalized Global Alignment Algorithm, Bioinformatics, 19: 228-233.
• Huang, X., Ye, L., Chou, H.-H., Yang, I-H. and Chao, K.-M. (2004) Efficient Combination of Multiple Word Models for Improved Sequence Comparison, Bioinformatics, 20: 2529-2533.
• Ye, L. and Huang, X. (2005) MAP2: Multiple Alignment of Syntenic Genomic Sequences. Nucleic Acids Research, 33: 162-170.
• Huang, X., Adams, M.D., Zhou, H. and Kerlavage, A.R. (1997) A Tool for Analyzing and Annotating Genomic Sequences. Genomics, 46: 37-45.
• Huang, X., Yang, S.-P., Chinwalla, A., Hillier, L., Minx, P., Mardis, E. and Wilson, R.  (2006) Application of a Superword Array in Genome Assembly,
  Nucleic Acids Research, 34: 201-205.
• Huang, X. and Brutlag, D.L. (2007) Dynamic Use of Multiple Parameter Sets in Sequence Alignment,
  Nucleic Acids Research, 35: 678-686.

Vita: Click here to download

Website: Xiaoqiu Huang

*Fred Janzen

Associate BCB Faculty Member

Education: Ph.D., Chicago, 1992

Research Interests: Modeling phenotypic selection, demography, phylogenetics

• Genome Evolution--Theoretical and empirical investigations of natural selection and phenotypic evolution; phylogenetic reconstruction and molecular evolution; modelling population demography and cycling environmental parameters

Description: Research interests in the Janzen Lab involve the study of ecology and evolution, including mechanistic work at the molecular and organismal levels, field studies that document the importance of phenotypic variation, and a comparative view of the long-term consequences of this variation. To do so, we often integrate molecular and quantitative genetic techniques with experimental laboratory and field studies, largely focusing on the impact of environmental and genetic factors in mediating the expression of physiological, behavioral, and life-history traits. Using these conceptual approaches in concert with comparative and computational approaches enables us to assess important biological issues, including

1. the biological significance of diverse sex-determining mechanisms,
2. the impacts of environmental and genetic factors on variation in early life-history traits, and
3. the current and historical genetic and demographic structure of populations, with an emphasis on elucidating adaptive processes and solving conservation concerns.

Selected Publications:

• Schwanz, L. E., and F. J. Janzen. 2008. Climate change and temperature-dependent sex determination: can individual plasticity in nesting phenology prevent extreme sex ratios? Physiological and Biochemical Zoology 81:in press.

• St. Juliana, J. R., and F. J. Janzen. 2007. Can natural phenotypic variances be estimated reliably under homogeneous laboratory conditions? Journal of Evolutionary Biology 20:1406-1414.
• Janzen, F. J., and P. C. Phillips. 2006. Exploring the evolution of environmental sex determination, especially in reptiles. Journal of Evolutionary Biology 19:1775-1784 .

• Janzen, F. J., and J. G. Krenz. 2004. Phylogenetics: Which was first, TSD or GSD? Pp. 121-130 in N. Valenzuela and V. A. Lance (eds.), “ Temperature-Dependent Sex Determination in Vertebrates.” Smithsonian Books, Washington, DC.

• Valenzuela, N., D. C. Adams, and F. J. Janzen. 2003. Pattern does not equal process: exactly when is sex environmentally determined? American Naturalist 161:676-683.

• Janzen, F. J. 1995. Experimental evidence for the evolutionary significance of temperature-dependent sex determination. Evolution 49:864-873.

Vita: Click here to download

Website: Fred Janzen

*Robert Jernigan

Education: Ph.D., Stanford, 1967

Research Interests: Computational structural biology and bioinformatics

• Macromolecular Structure and Function-- theoretical and computational studies of the structures of proteins, nucleic acids, and small molecules, and their interactions. Applications are made to develop molecular models and to select new drugs. more

Description: Elastic network models of bio-structures are used to develop mechanisms of processing, refine and improve structures, predict conformational transitions. Applications to learn about the mechanics of the ribosome are pursued. Sequence matching is being improved by including structural information and to improve comparative genomics efforts.

• Cui, F, Jernigan, R, Wu, Z Knowledge-based versus experimentally acquired distance and angle
  constraints for NMR structure refinement. J Bioinform Comput Biol 2008;6:283-300.
• Yang L, Song G, Jernigan RL How well can we understand large-scale protein motions using elastic
  normal modes? Biophys J 2007; 93:920-929.
• Wu D, Cui F, Jernigan R, Wu, ZJ PIDD: Database for protein inter-atomic distance distributions. Nucl
  Acids Res 2007;35:D202-D207.
• Miyazawa, S. and Jernigan, R.L. Estimation of effective inter-residue contact energies from protein
  crystal structures: quasi-chemical approximation. Macromolecules 1985; 18: 534-552.
• Pokarowski, P., Kloczkowski, A., Jernigan, R.L., Kothari, N.S., Pokarowska, M. and Kolinski, A.
  Inferring ideal amino acid interaction forms from statistical protein contact potentials, Proteins: Struct.
  Funct. Bioinf. 2005; 59: 49-57.

Vita: Click here to download

Website: Robert Jernigan

Douglas Jones

Associate BCB Faculty Member

Education: Ph.D., University of Pennsylvania, 1993

Research Interests: Host factors that influence the development of resistance and susceptibility to infectious diseases caused by intracellular pathogens

• Macromolecular Structures and Functions--Dr. Jones researches the host factors that influence the development of resistance and susceptibility to infectious diseases caused by intracellular pathogens. The laboratory studies the murine immune response to the protozoal parasite Leishmania and the bovine immune response to Mycobacterium avium subs paratuberculosis

Description:

Selected Publications:

Vita: Click here to download

Website: Doug Jones

Susan Lamont

Associate BCB Faculty Member

Education: Ph.D., Illinois Medical Center, 1980

Research Interests: Molecular markers, gene expression, quantitative trait loci, biodiversity. Structural and functional genomic associations with biological traits

• Functional and Structural Genomics--Molecular genetic dissection of complex biological traits in poultry. Structural and functional genomics
• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking-- Estimation of genetic relationships by molecular analysis; characterization of gene regulatory regions; mathematical modelling and genetic dissection of complex biological traits; estimating epistatic effects of molecular markers

Description: Dr. Lamont's program investigates the associations of structural and functional genomic variation with complex biological traits in poultry.  Taking advantage of the complete draft genome sequence of the chicken genome, a 2.8-million SNP map, and unique genetic resource populations at Iowa State, specific projects seek to dissect the complex genetic architecture of traits such as disease resistance, growth and development.

Selected Publications:

• Ye, X., Brown, S.R., Nones, K., Coutinho, L.L., Dekkers, J.C.M. and Lamont. S.J. 2007. Associations of myostatin gene polymorphisms with performance and mortality traits in broiler chickens. Genet. Sel. Evol. 39: 73-89.
• Zhou, H., Deeb, N., Evock-Clover, C., Mitchell, A., Ashwell, C. and Lamont, S.J. 2007. Genome-wide Linkage Analysis to identify chromosomal regions affecting phenotypic traits in the chicken. III. Skeletal integrity. Poultry Sci. 86:255-266.
• Zhou, H., Evock-Clover, C., McMurtry, J.P., Ashwell, C. and Lamont, S.J. 2007. Genome-wide Linkage Analysis to identify chromosomal regions affecting phenotypic traits in the chicken. IV. Metabolic traits. Poultry Sci. 86:267-276.
• Abasht, B. Dekkers, J.C.M, and Lamont, S.J. 2006. Review of quantitative trait loci Identified in the chicken. Poultry Sci. 85:2079-2096.
• Cheeseman, J.H., Kaiser, M.G., Ciraci, C., Kaiser, P. and Lamont, S.J. 2006. Breed effect on early cytokine mRNA expression in spleen and cecum of chickens with and without Salmonella enteritidis infection. Devel. Comp. Immunol. 31: 52-60.
• Hangalapura, B. N., Kaiser, M. G., van der Poel, J.J., Parmentier, H. K., and Lamont, S. J. 2006. Cold stress equally enhances in vivo pro-inflammatory cytokine gene expression in chicken lines divergently selected for antibody responses. Develop. Comp. Immunol. 30:503-511.
• Hasenstein, J.R., Zhang, G., and Lamont, S.J. 2006. Analyses of five gallinacin genes and the Salmonella enterica serovar enteritidis response in poultry. Infection & Immunity 74:3375-3380.
• Kaiser, M.G., J.H. Cheeseman, Kaiser, P., and Lamont, S.J. 2006. Cytokine expression in chicken peripheral blood mononuclear cells after in vitro exposure to Salmonella enterica serovar Enteritidis. Poultry Sci 85:1907-1911. Lamont, S.J. 2006. Perspectives in chicken genetics and genomics. Poultry Sci. 85:2048-2049.
• Wick, G., Andersson, L., Hala, K., Gershwin, M. E., Selmi, C.F., Erf, G. F., Lamont, S.J., and Sgonc, R. 2006. Avian models with spontaneous autoimmune diseases. Pp. 71-117. In: Advances in Immunology. F.W. Alt, Ed. Elsevier/Academic Press, San Diego, CA
• McElroy, J.P., Kim, J.J., Harry, D.E., Brown, S.R., Dekkers, J.C., and Lamont, S.J. 2006. Identification of trait loci affecting white meat percentage and other growth and carcass traits in commercial broiler chickens. Poultry Sci. 85:593-605.
• McElroy, J.P., Zhang, W., Koehler, K.J., Lamont, S.J., and Dekkers, J.C.M. 2006. Comparison of methods for analysis of selective genotyping survival data. Genetics Selec. Evol. 38:637-655.
• Soller, M., Weigend, S., Romanov, M.N., Dekkers, J.C.M., and Lamont, S.J. 2006. Strategies to assess structural variation in the chicken genome and its associations with biodiversity and biological performance. Poultry Sci. 85:2061-2078.
• Ye, X., Avendano, S., Dekkers, J.C.M. and Lamont, S.J. 2006. Association of twelve immune-telated genes with performance of three broiler lines in two different hygiene environments. Poultry Sci. 85:1555-1568.
• Ye, X., McLeod, S., Elfick, D., Dekkers, J.C.M., and Lamont, S.J. 2006. Rapid identification of single nucleotide polymorphisms and estimation of allele frequencies using sequence traces from DNA pools. Poultry Science 85: 1165-1168.
• Zhou, J., Deeb, N., Ashwell, C.M., and Lamont, S.J. 2006. Genome-wide linkage analysis to identify chromosomal regions affecting phenotypic traits in the chicken. I. Growth and average daily gain. Poultry Sci. 85:1700-1711.
• Zhou, J., Deeb, N., Ashwell, C.M., and Lamont, S.J. 2006. Genome-wide linkage analysis to identify chromosomal regions affecting phenotypic traits in the chicken. II. Body composition. Poultry Sci. 85: 1712-1721.

Website: Susan Lamont

*Dennis Lavrov

Education: Ph.D., University of Michigan, Ann Arbor, 2000

Research Interests: My main research interests are the evolution of major groups of animals and their mitochondrial genomes.  My current research is focused on three groups of non-bilaterian animals: Cnidaria, Ctenophora, and Porifera.  Ongoing projects include: Comparative animal mitochondrial genomics; Parallel mitochondrial genome evolution; Phylogenetic analysis of basal animal relationships; and Cell-cell communication in sponges.

• Bioinformatics--Molecular evolution, phylogenetics, comparative and functional genomics; use of gene order data for the analysis of ancient relationships; evolution of animal mitochondrial DNA with a special emphasis on arthopods and sponges; bioinformatics
• Functional and Structural Genomics--Same as above
• Genome Evolution--Same as above

Description:

Selected Publications:

• Lavrov, D. V. 2007. Key transitions in animal evolution: a mitochondrial DNA perspective.  Integrative and Comparative Biology. 47:734-743.
• Haen, K. M., Lang, B. F., Pomponi, S. A. and Lavrov D. V. 2007. Mitochondrial genomes of the glass sponges Iphiteon panicea and Sympagella nux (Hexactinellida, Plakinidae): an evidence of the bilaterian affinity or an example of parallel evolution? Molecular Biology and Evolution. 24:1518-1527.
• Wang, X. and D. V. Lavrov 2007. Mitochondrial Genome of the Demosponge Oscarella carmela (Porifera, Demospongiae) Reveals Unexpected Complexity in the Common Ancestor of Sponges and Other Animals  Molecular Biology and Evolution.  24: 363-373.
• Lavrov, D. V. and B. F. Lang, 2005.  Transfer RNA gene recruitment in mitochondrial DNA.  Trends in Genetics.  21:129-133.
• Lavrov D.V. and Lang B.F. 2005 Poriferan mtDNA and animal phylogeny based on mitochondrial gene arrangements Systematic Biology 54:651-659.
• Lavrov D.V., Forget L., Kelly, M., and Lang B.F. 2005 Mitochondrial genomes of two demosponges provide insights into an early stage of animal evolution Mol. Biol. Evol. 22:1231-1239.

Vita: Click here to download

Website: Dennis Lavrov

Carolyn Lawrence

Education: Ph.D., The University of Georgia, 2003

Research Interests: My group manages the operation of the Maize Genetics & Genomics Database (MaizeGDB) and also investigates functional aspects of maize chromosomes during cell division. The work at MaizeGDB is focused on creating data storage, access, and analysis solutions for information generated by the community of maize geneticists. The maize chromosome research focuses on how chromosome move and how the physical structure of chromosomes relates to maps and DNA sequences. http://www.lawrencelab.org

Selected Publications:

• L.D. Stein, W.D. Beavis, D.D. Gessler, E. Huala, C.J. Lawrence, D. Main, L.A. Mueller, S.Y. Rhee, and D.S. Rokhsar, Save our data!, The Scientist 20(4):24-25, 2006.
• Lawrence, C.J. and Walbot, V. Maize as a model for bioenergy production from fuelstock grasses. The Plant Cell 19(7):2091-2094. 2007.
• Duvick, J., Fu, A., Muppirala, U., Sabharwal, M., Wilkerson, M.D.,  Lawrence, C.J., Lushbough, C., and Brendel, V. PlantGDB: a resource for comparative plant genomics. Nucleic Acids Research 36(Database issue):D959-965. 2008.
• Lawrence, C.J. MaizeGDB, the maize genetics and genomics database. In Plant bioinformatics, D. Edwards (Editor) for the series Methods in Molecular Biology. pp. 331-345. Humana Press, Totowa, New Jersey, USA. 2007.
• Lawrence, C.J. and Walbot, V. Reply: specific reasons to favor maize in the U.S. Plant Cell 19(10):2973. 2007.
• Lawrence, C.J. and Ware, D. Databases and data mining. In The maize handbook, S. Hake and J. Bennetzen (Editors), Springer. Accepted October 15, 2007.
• Harper, L.C., Sen, T.Z., and Lawrence, C.J. Plant cytogenetics in genome databases. In: Plant cytogenetics: genome structure and chromosome function. J. Birchler and H. Bass (Editors), Springer.  Accepted October 30, 2007.

Website: Carolyn Lawrence

Howard Levine

Education: Ph.D., Cornell, 1969

Research Interests: Modeling of angiogenesis and tumor growth, chemotaxis in biological systems. Mathematical modeling of transport and branching processes in biological systems

• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking-- Mathematical modeling of biological branching processes including angiogenesis, vasculogenesis, neuronal growth, mammary duct development involving cell-cell and intra cellular signal transduction pathways.

Selected Publications:

• Levine, H. A. and M. Nilsen-Hamilton A mathematical analysis of SELEX, Journal of Computational Biology and Chemistry , 31 (2007) 11-35 K.
• Boushaba, Levine, H. A and Nilsen-Hamilton, M., A mathematical model for the regulation of metastatic tumor dormancy based on enzyme kinetics, Bull. Math. Biol., 68, 2006, 1-32.
• Levine, H. A. and Smiley, M. W. , Tucker, A. and Nilsen-Hamilton, M) A mathematical model for the formation of avascular tumors based on the role of the p53 tumor suppressor gene, Cancer Informatics, 2, 2006 , 163-188.
• Levine, H. A. and M. Nilsen-Hamilton, Angiogenesis-A Biochemical/Mathematical Perspective, Chapter 2., in Tutorials in mathematical biosciences: Cell cycle, proliferation, and cancer (Vol. 3). A. Friedman,ed., Springer-Verlag, Berlin, Heidelberg, New York , 2006.
• Levine, H. A. , Renclawowicz, J., Singularity formation in chemotaxis - A conjecture of Nagai\jour( SIAM J. Appl. Math., ) 65(1) , 2004, 336-362 Hillen , T. and Levine, H. A. Blow up and pattern formation in hyperbolic models for chemotaxis, ZAMP 54, 2003 839-868.
• Levine, H. A., Tucker, A. and Nilsen-Hamilton, M., A mathematical model for the role of cell signal transduction in the initiation and inhibition of angiogenesis, Growth Factors, 20(4), 2002, 155-175.
• Levine, H. A. and Sleeman, B.,D. Modelling Tumour Induced Angiogenesis, Chapter 6, in: Cancer Modelling and Simulation, L. Preziozi, eds., Chapman and Hall/CRC Press, 2003, pp. 147-183. Levine, H. A., Pamuk, S., Sleeman, B. D. and Nilsen-Hamilton, M., Mathematical modeling of capillary formation and development in tumor angiogenesis: penetration into the stroma, Bull. Math. Biol., 63(5), 2001, 801-863.
• Levine, H. A., S. Pamuk, B. D. Sleeman and Nilsen-Hamilton, M. Mathematical modelling of tumor angiogenesis and the action of angiostatin as a protease inhibitor, J. Theoret. Med. 4(2) 2002 133-145.
• Levine, H. A., Sleeman, B. D. and Nilsen-Hamilton, M., Mathematical Modeling of the initiation of capillary formation initiating angiogenesis, J. Math. Biol., 42(3), 2001, 195-238.
• Levine, H. A., Sleeman, B. D. and Nilsen-Hamilton, M., A mathematical model for the roles of pericytes and macrophages in the initiation of angiogenesis: I. The role of protease inhibitors in preventing angiogenesis., Mathematical Biosciences, 168, 2000, 77-115.

Vita: Click here to download

Website: Howard Levine

*Peng Liu

Associate BCB Faculty Member

Education: Ph.D., Cornell University, 2006

Research Interests: Functional and Structural Genomics-- Statistical design and analysis of microarray experiments, statistical methods for high-dimensional data including gene expression data and proteomic data.

Publications:

• P. Liu and J. T. G. Hwang (2007), Quick estimation of sample size while controlling false discovery rate and application to microarray analysis, Bioinformatics, 23(6): 739-746
• R. J. H. Sawers, P. Liu, K. Anufrikova, Q. Sun, G. Olsefski, J. T. G. Hwang, T. Brutnell (2007), Gene expression profiling of bundle sheath and mesophyll photosynthetic cell-types of maize, BMC genomics, 8:12
• S. A. Jesch, P. Liu, X. Zhao, M.  T. Wells, and S. A. Henry (2006), Multiple endoplasmic reticulum-localized protein complexes respond to phospholipid metabolism and regulate gene expression by distinct mechanisms, Journal of Biological Chemistry, 281: 24070 - 24083

Vita: Click here to download

Website: Peng Liu

*Gustavo MacIntosh

Associate BCB Faculty Member

Education: Ph.D., University of Buenos Aires, 1997

Research Interests: My laboratory is engaged in understanding the interaction between plants and pests. We use different approaches to study this problem, including metabolomics and transcriptomics analyses. We then use bioinformatics tools to analyze the large amount of data generated. While not fully there yet, we are working towards a “systems biology” interpretation and model generation of these interactions. Another area of research in my laboratory is the analysis of protein structure/function and the acquisition of novel functions by duplicated genes during evolution. Bioinformatics tools are also used in this project, from phylogenetic analysis to protein threading and structure prediction.

Selected Publications:

1. Hillwig MS, Rizshsky L, Wang Y, Umanskaya A, Essner JJ, MacIntosh GC (2008) Zebrafish RNase T2 genes and the evolution of ribonucleases in animals. Submitted to Mol. Biol. Evol.

2. Hillwig MS, LeBrasseur ND, Green PJ and MacIntosh GC (2008) Impact of transcriptional, ABA-dependent, and ABA-independent pathways on wounding regulation of RNS1 expression. Mol. Gen. Genom. 280: 249-261

3. Raices M, MacIntosh GC, Ulloa RM, Gargantini PR, Vozza NF, Tellez-Inon MT (2003) Sucrose increases calcium-dependent protein kinase and phosphatase activities in potato plants. Cell Mol Biol 49: 959-964

4. Raices M, Ulloa RM, MacIntosh GC, Crespi M and Tellez-Inon MT (2003) StCDPK1 is expressed in potato stolon tips and is induced by high sucrose concentration. J. Exp. Bot. 54: 2589-2591.

5. LeBrasseur ND, MacIntosh GC, Pérez-Amador MA, Saitoh M and Green PJ (2002) Local and systemic wound-induction of RNase and nuclease activities in Arabidopsis: RNS1 as a marker for a JA-independent systemic signaling pathway . Plant J., 29: 393-403.

Vita: Click here to download

Website: Gustavo MacIntosh

*Leslie Miller

Education: Ph.D., SMU, 1980

Research Interests: Multidatabases for biology data sources, biological data warehouse

• Bioinformatics-- Multidatabases for biology data sources; biological data warehouses; protein structure prediction

Selected Publications

• Fu, Fengli, Jeffry Sander, Morgan Maeder, Stacy Thibodeau-Beganny, J. Joung, Drena Dobbs, Leslie Miller, Daniel Voytas. (2008). Zinc Finger Database (ZiFDB): a repository for information on C2H2 zinc fingers and engineered zinc finger arrays. To appear in the database Nucleic Acids Research issue.
• Miller, Les, Sree Nilakanta, and Meghana Rao. (2008). Supporting Knowledge Management Within Process and Group Settings Using Visual Topic Maps. ISCA 23rd International Conference on Computers and Their Applications (CATA-2008). April 9-11, 2008. Cancun, Mexico.
• L. Miller, S. Nilakanta, Y. Song, L. Zhu, M. Hua. 2008. Managing Knowledge in Organizational Memory Using Topic Maps. International Journal of Knowledge Management, IGI Publishing. Vol. 4. No. 1. pp. 17-28.
• Wurtele, E.S., L. Li, D. Berleant, D. Cook, J.A. Dickerson, J. Ding, H. Hofmann, M. Lawrence, E.K. Lee, J. Li, W. Mentzen, L. Miller, B.J. Nikolau, N. Ransom, Y. Wang, (2007). MetNet: Systems Biology Software for Arabidopsis. In: Concepts in Plant Metabolomics. Springer. pp 145-158.
• Miller, Les, Hua Ming, Hsine-Jen Tsai, Becca Wemhoff and Sarah Nusser. 2007. Supporting
  Geographic Data in the Mobile Computing Environment. ISCA 20th International Conference on Parallel
  and Distributed Computing Systems. Las Vegas, NV. pp. 56-61.

Vita: Click here to download

Website: Leslie Miller

Allen Miller

Associate BCB Faculty Member

Education: Ph.D., Wisconsin, Madison, 1984

Research Interests: We study molecular biology of plant RNA viruses with three different but overlapping perspectives

• Functional and Structural Genomics-- Prediction of RNA secondary and tertiary structure; plant virus genome sequencing and database, novel translation mechanisms
• Macromolecular Structure and Function-- Same as above

Description:

RNA virus replication:  from plants to humans

We employ plant viruses as easy-to-use model systems to provide basic understanding of how viruses replicate and express genes.  Because of similarities in replication mechanisms across kingdoms, this knowledge may be relevant to major human viruses. Viruses are fascinating as the smallest, minimal replicating entities.  They allow detailed understanding of what it takes to replicate, the essential property that defines life.

How cells decode the genetic code

We investigate the plethora of tricks by which viral messenger RNA usurps and controls the host translational machinery (translation factors and ribosomes).  This gives us a better understanding of fundamental mechanisms of protein synthesis.  This knowledge may allow us to modify viral sequences and mechanisms to control expression of host and viral genes in beneficial ways.

Sustainable control of crop diseases and pests

We strive to improve the knowledge base needed to control the economically important yellow dwarf viruses and the aphids that transmit them.  They vary remarkably in sequence.  We are determining complete nucleotide sequences of dozens of virus isolates from around the world.  We are also attempting to exploit aphid viruses, and aphid-transmitted plant viruses, to control aphids in cereal crops and soybeans.

Selected Publications:

• Chung BY-W, Miller WA, Atkins JF, Firth AE (2008) An overlapping essential gene in the Potyviridae. Proc Natl Acad Sci USA 105, 5897-5902.
• Treder K, Pettit Kneller EL, Allen EM, Wang Z, Browning KS, Miller WA (2008) The 3’ cap-independent translation element of Barley yellow dwarf virus binds eIF4F via the eIF4G subunit to initiate translation. RNA 14, 134-147.
• Miller WA, Wang Z, Treder K (2007) The amazing diversity of cap-independent translation elements in the 3’-untranslated regions of plant viral RNAs. Biochemical Society Transactions 35, 1629-1633.

Vita: Click here to download

Website: W. Allen Miller

Chris Minion

Associate BCB Faculty Member

Education: Ph.D., Alabama, Birmingham, 1983

Research Interests: Microbial pathogenomics, gene regulation

• Functional and Structural Genomics-- Analysis of genome sequence data; motif signatures; protein structure prediction; gene regulatory regions

Description: Dr. Minion's research interests focus on the molecular basis of pathogenesis and persistence of bacterial pathogens in domestic animals. Major emphasis is on pathogenomics, identification of virulence factors, gene profiling, and development of molecular vaccines in mycoplasmas. His laboratory also studies the molecular basis of persistence of Escherichia coli O157:H7 in ruminants and Salmonella enteritidis in poultry using genetic tools such as signature tagged mutagenesis. Microarray studies are being conducted in Mycoplasma hyopneumoniae, E. coli O157:H7 and L. monocytogenes to understand bacterial in vivo gene expression and its relationship to virulence. Comparative genomics and genome sequencing is being performed to identify virulence factors in mycoplasmas.

KEY WORDS: Microbial virulence, bacterial genetics, food safety, bacterial gene regulation, molecular vaccines, bacteria-host interactions, gene profiling, swine, respiratory diseases, sheep.

Selected Publications:

• Menon, S. A. M., J. Wannemuehler, G. G. Mahairas, and F. C. Minion. 2002. Mycobacterial ESAT-6 protein enhances mouse interferon- responses to Mycoplasma hyopneumoniae P71 protein. J. Interf. Cytok. Res. 22:807-813.
• Minion, F.C., S.A. Menon, G.G. Mahairas, and M.J. Wannemuehler. 2003. Enhanced murine antigen-specific IFN- g responses using mycobacterial ESAT-6 sequences in DNA vaccines. Infect. Immun. 71:2239-2242.
• Matic, J.N., J.L. Wilton, R.J. Towers, A.L. Scarman, F.C. Minion, M.J. Walker and S.P. Djordjevic . 2003. The pyruvate dehydrogenase complex of Mycoplasma hyopneumoniae contains a novel lipoyl domain arrangement. Gene 319:99-106.
• Djordjevic, S. P., S. J. Cordwell, M. A. Djordjevic, J. Wilton, and F. C. Minion. 2004. Proteolytic processing of the Mycoplasma hyopneumoniae cilium adhesin. Infect. Immun. 72:2791-2802.
• Minion, F. C., E. L. Lefkowitz, M. L. Madsen, B J. Cleary, S. M. Swartzell, and G. G. Mahairas. 2004. The genome sequence of Mycoplasma hyopneumoniae strain 232, the agent of swine mycoplasmosis. J. Bacteriol. 186:7123-7133.
• Adams, C., J. Pitzer, and F. C. Minion. 2005. In vivo expression analysis of the P97 and P102 paralog families of Mycoplasma hyopneumoniae. Infect. Immun. 73:7784-7787.
• Madsen, M. L., D. Nettleton, E. L. Thacker, R. Edwards, and F. C. Minion. 2006. Transcriptional profiling of Mycoplasma hyopneumoniae during heat shock using microarrays. Infect. Immun. 74: 167-174.
• Jenkins, C., J. L. Wilton, F. C. Minion, L. Falconer, M. J. Walker, and S. P. Djordjevic. 2006. Two domains within the Mycoplasma hyopneumoniae cilium adhesin bind heparin. Infect. Immun. 74:481-487.
• Burnett, T.A., K. Dinkla, M. Rohde, G.S. Chhatwal, M. Srivastava, S.J. Cordwell, S. Geary, F. C. Minion,. M. J. Walker, S. P. Djordjevic. 2006. P159 is a proteolytically processed, surface adhesin of Mycoplasma hyopneumoniae: defined domains of P159 bind heparin and promote adherence to eukaryotic cells. Mol. Microbiol. 60:669-686.
• Madsen, M. L., D. Nettleton, E. L. Thacker, and F. C. Minion. 2006. Transcriptional profiling of Mycoplasma hyopneumoniae during iron depletion using microarrays. Microbiology 152:937-944.
• Schafer, E. R., M. J. Oneal, M. L. Madsen, F. C. Minion. 2007. Global transcriptional analysis of Mycoplasma hyopneumoniae following exposure to hydrogen peroxide. Microbiol. 153:3785-3790.
• Madsen, M. L., M. J. Oneal, S. W. Gardner, E. L. Strait, D. Nettleton, E. L. Thacker, and F. C. Minion. 2007.Array-based genomic comparative hybridization of field strains of Mycoplasma hyopneumoniae. J. Bacteriol. 189:7977-7982.
• Vicca, J., D. Maes, T. Stakenborg, P. Butaya, F. Minion, J. Peeters, A. De Kruif, A. Decostere, and F. Haesebrouck. 2007. Resistance mechanism against fluoroquinolones in Mycoplasma hyopneumoniae field isolates. Microb. Drug Resist. 13:166-170.
• Madsen, M. L., S. Puttamreddy, E. L. Thacker, M. D. Carruthers, F. C. Minion. 2008. Transcriptome changes in Mycoplasma hyopneumoniae during infection. Infect. Immun. 76:658-663.
• Chang, L.-J., W.-H. Chen, F. C. Minion and D. Shiuan. 2008. Mycoplasmas regulate the expression of heat shock protein genes through CIRCE-HrcA interactions. Biochem. Biophys. Res. Commun. 367:213-218.

Vita: Click here to download

Website: Chris Minion

Kirk Moloney

Associate BCB Faculty Member

Education: Ph.D., Duke, 1986

Research Interests: Spatial ecology, ecological modeling, invasive species

• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking-- Modeling the dynamics of spatial processes in ecological systems; analysis of spatial pattern; disturbance ecology; spatial ecology of invasions; complexity in ecological systems

Description: (1) experimental and observational studies of plant and animal populations and communities in a spatial context; (2) development of spatially explicit simulation models as experimental tools for studying fundamental ecological relationships in a spatial context; and (3) development of analytical techniques for characterizing pattern over a range of spatial and temporal scales as a means of identifying critical, pattern forming ecological processes

Selected Publications:

• Martin, L. M,. K. A. Moloney and B. J. Wilsey. In press. An assessment of grassland restoration success using species diversity components. Journal of Applied Ecology
• Eccard JA, Dean WRJ, Wichmann MC , Moloney KA, Jeltsch F. In press Use of large Acacia trees by the cavity dwelling Black-tailed Tree Rat in the Southern Kalahari . Journal of Arid Environments.
• Wiegand T. , E. Revilla, and K.A. Moloney. 2005. Effects of habitat loss and fragmentation on population dynamics. Conservation Biology 19(1):108-121.

Vita: Click here to download

Website: Kirk Moloney

*Dan Nettleton

Education: Ph.D., Iowa, 1996

Research Interests: Statistical design and analysis of microarray experiments, statistical methods for mapping QTL

• Functional and Structural Genomics-- Statistical design and analysis of gene expression experiments; Statistical methods for mapping quantitative trait loci

Description:

Selected Publications:

• Nettleton, D. (2006). A Discussion of statistical methods for design and analysis of microarray experiments for plant scientists. The Plant Cell. 18 2112-2121.
• Wang, D., Nettleton, D. (2006). Identifying genes associated with a quantitative trait or quantitative trait locus via selective transcriptional profiling. Biometrics. 62 504-514.
• Nettleton, D., Hwang, J.T.G., Caldo, R.A., Wise, R.P. (2006). Estimating the number of true null hypotheses from a histogram of p-values. Journal of Agricultural, Biological, and Environmental Statistics. 11 337-356.

Vita: Click here to download

Website: Dan Nettleton

*Basil Nikolau

Associate BCB Faculty Member

Education: Ph.D., Massey University, New Zealand, 1982

Research Interests: Functional genomics of metabolism, metabolic modeling and metabolic networks.

• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking-- Biochemistry and molecular biology of biotin and biotin-containing enzymes; Regulation of plant lipid metabolism

Description:

Selected Publications:

• Dietrich, C.R., Perera, M.A., M, D.Y.-N., Meeley, R.B., Nikolau, B.J.and Schnable, P.S. (2005) Characterization of two GL8 paralogs reveals that the 3-ketoacyl reductase component of fatty acid elongase is essential for maize (Zea mays L.) development. Plant J. 42,844-861.
• Fatland, B.L., Nikolau, B.J. and Wurtele, E.S. (2005) Reverse genetic characterization of cytosolic acetyl-CoA generation by ATP-Citrate lyase in Arabidopsis. Plant Cell 17, 182-203. Yandeau-Nelson, M.D., Zhou, Q., Yao, H., Xu, X., Nikolau, B.J. and Schnable, P.S. (2005) MuDR transposase increases the frequency of meiotic crossovers in the vicinity of a Mu insertion in the maize a1 gene. Genetics 169, 917-929.
• Sluszny, C., Yeung, E.S. and Nikolau, B.J. (2005) In-situ probing of the biotic-abiotic boundary of plants by laser desorption/ionization time-of-flight mass spectrometry. J. Am. Soc. Mass. Spectrom. 16, 107-115.

Vita: Click here to download

Website: Basil Nikolau

Marit Nilsen-Hamilton

Education: Ph.D., Cornell, 1973

Research Interests: Gene expression, aptamers, imaging, modeling biology

• Functional and Structural Genomics-- Regulation of gene expression, the application of functional nucleic acids (aptamers and ribozymes) to medicine and microanalysis.
• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking-- In collaboration with Boushaba,  Levine and Smiley, modeling biochemical processes, cell movement and differentiation.  In collaboration with Lamm, modeling molecular structure and molecular movement.

Description: Using biochemical, molecular, cellular, and developmental approaches, which include purifying the proteins, cloning the genes, determining their sequences, identifying the relevant regulatory elements, and identifying new transcriptional regulators

Selected Publications:

• Determan, A.S., Trewyn, B.G., Lin, V.S., Nilsen-Hamilton, M. and Narasimhan, B. (2004) Encapsulation, stabilization, and release of BSA-FITC from polyanhydride microspheres. J. Control. Release 100, 97-109.
• Nilsen-Hamilton, M., Liu, Q., Ryon, J., Bendickson, L., Lepont, P. and Chang, Q. (2003) Tissue involution and the acute phase response. Ann. NY Acad. Sci. 995, 94-108.
• Ryon, J., Bendickson, L. and Nilsen-Hamilton, M. (2002) High expression in involuting reproductive tissues of uterocalin/24p3, a lipocalin and acute phase protein. Biochem. J. 367, 271-277.

Vita: Click here to download

Website: Marit Nilsen-Hamilton

Thomas Peterson

Associate BCB Faculty Member

Education: Ph.D. California, Santa Barbara, 1984

Research Interests: Transposons elements, genome rearrangements

• Functional and Structural Genomics-- Characterization and prediction of gene regulatory regions; computational reduction of primary genomic sequence data to composite elements; computational analysis of regulatory information encoded in DNA base modifications, e.g. methylation

Description:

Selected Publications:

• Cocciolone, S.M., Nettleton, D., Snook, M.E., and T. Peterson. 2005. Transformation of maize with the p1 transcription factor directs production of silk maysin, a corn earworm resistance factor, in concordance with a hierarchy of floral organ pigmentation. Plant Biotechnology Journal 3: 225-235.
• Zhang, F. and T. Peterson. 2005. Comparisons of maize pericarp color 1 alleles reveal paralogous gene recombination and an organ-specific enhancer region. The Plant Cell 17: 903 ­ 914.
• Zhang, J. and T. Peterson. 2005. A Segmental Deletion Series Generated by Sister Chromatid Transposition of Ac Transposable Elements in Maize. Genetics 2005: doi: 10.1534/genetics.104.035576.
• Boddu, J., Sangar, V., Jiang, C., Olson, T., Peterson, T., and S. Chopra. Comparative structural and functional characterization of sorghum and maize duplications containing orthologous Myb transcription regulators of 3-deoxyflavonoid biosynthesis. (Plant Mol. Biol., accepted).
• Zhang, F. and T. Peterson. Gene conversion between direct non-coding repeats promotes genetic and phenotypic diversity at a regulatory locus of Zea mays (L.) Genetics, in press
• Zhang, J., Zhang, F., and T. Peterson. Transposition of Reversed Ac Element Ends Generates Novel Chimeric Genes in Maize. PLoS Genetics, in press.

Vita: Click here to download

Website: Agronomy: Thomas Peterson; GDCB Page

*Gregory Phillips

Associate BCB Faculty Member

Education: Ph.D., University of Georgia, Athens, 1987

Research Interests: Use of genomic approaches to determine gene function in pathogenic bacteria

• Macromolecular Structure and Function-- Our research includes understanding how the structure of the signal recognition particle (SRP) contributes to its function to target proteins to the cytoplasmic membrane in bacteria, and use of genomic approaches to determine gene function in pathogenic bacteria

Description:

Selected Publications:

• Schmidt K, L,, N. D. Peterson, R. J. Kustusch, M. C. Wissel, B. Graham, G. J. Phillips, D. S. Weiss 2004. A predicted ABC transporter, FtsEX, is needed for cell division in Escherichia coli. J. Bacteriol. 186:785-793.
• Platt, R., Reynolds, D. L., Phillips, G. J. 2003. Development of a novel method of lytic phage delivery by use of a bacteriophage P22 site-specific recombination system. FEMS Microbiol. Lett. 2003 223:259-265.

Vita: Click here to download

Website: Gregory Phillips

Krishna Rajan

Education: Sc.D., MIT, 1978.

Research Interests: Linking bioinformatics with materials informatics.

Publications:

• Learning from Systems Biology: An “omics” approach to materials design JOM 53-55 (March 2008)
• Repression of the “Host-Adapted” phenotype of Francisella tularensis: implications for basic and applied research : K.R. O. Hazlett, S. D. Caldon, D. G. McArthur, K. A. Cirillo, G. S. Kirimanjeswara, M. L. Magguilli, M.Malik, A. Shah, S. Broderick, I. Golovliov, D.W. Metzger, K. Rajan, T.J. Sellati, and D. J. Loegering Infect. Immun.76: 4479-4488 (2008)
• Combinatorial Materials Sciences: Experimental Strategies for Accelerated Knowledge Discovery; Annual Reviews of Materials Research vol 347 , (August 2008)
• Scientific Data Analysis : C. Kamath, N.Wade, G. Karypis, G. Pandey, V. Kumar, K. Rajan, N.F. Samatova,P. Breimyer, G. Kora, C. Pan and S. Yoginath in Scientific Data Management eds. A. Shoshani and D. Rotem, Taylor and Francis (2008)
• Combinatorial Methods and Informatics Provide Insight into Physical Properties and Structure Relationships during IPN Formation J. Nowers, S.R.Broderick, K.Rajan and B. Narasimhan:: Macromolecular Rapid Communications 28 972-976 (2007)

Vita: Click here to download

Website: http://mse.iastate.edu/cosmic/why2.html

James Reecy

Education: Ph.D., Purdue, 1995

Research Interests: Regulation of gene expression, gene discovery, skeletal muscle growth, microarray analysis

• Bioinformatics – Development of livestock genomics databases to facilitate discovery of gene function; Annotation of the cattle genome
• Functional and Structural Genomics-- Identification of genes controlling skeletal muscle growth and development; Application of whole genome selection methodology to improve healthfulness of beef, resistance to disease, and growth.

Description: My research interests cut across Animal Science, Genetics, and Information Sciences. This research is driven by fundamental scientific questions or important practical problems such as the following:

• How can we facilitate the discovery of gene function?
• How can we build useful tools/databases to aid molecular geneticists?
• How can we develop ontologies to facilitate effective communication between scientists?
• How can we identify molecular markers that are associated with traits of interest?
• How can we use whole genome selection to improve society (e.g. can we select for the production of food that is healthier to eat)?
• Can we identify livestock species specific genes?

Selected Publications:

• Zhi-Liang, H., E.R. Fritz, and J.M. Reecy. 2006. AnimalQTLdb: A Livestock QTL Database Tool Set for Positional QTL Information Mining and Beyond. Nucleic Acid Research Database issue doi:10.1093/nar/gkl946. Nucleic Acid Research 35(Database issue):D604-9.
• Zhi-Liang, H., and J.M. Reecy. 2007. Animal QTLdb: Beyond a Repository – A Public Platform for QTL Comparisons and Integration with Diverse Types of Structural Genomic Information. Mammalian Genome 18(1):1-4.
• Tuggle, C.K., J.C.M. Dekkers, and J.M. Reecy. 2006. Integration of structural and functional Genomics. Animal Genetics 37:(Supplement 1):1-6.
• Tantia, M.S., R.K. Vijh, S.T. Bharani Kumar, B. Mishra, and J.M. Reecy. 2006. Comparative analysis of GDF 8 (myostatin) in Bos indicus and Bos Taurus. DNA Sequence 17(4):311-3.
• Bao, J., Z. Hu, D. Caragea, J.M. Reecy, and V. Honavar. A Tool for Collaborative Construction of Large Biological Ontologies. Fourth International Workshop on Biological Data Management (BIDM 2006), Krakov, Poland, IEEE Press. pp. 191-195
• Steelman, C. A., J.C. Recknor, D. Nettleton, and J.M. Reecy. 2006. Transcriptional profiling of myostatin-knockout mice implicates Wnt signaling in postnatal skeletal muscle growth and hypertrophy. FASEB Journal 20(3):580-582. Epub 2006 Jan 19.
• Steelman, C.A., J.C. Recknor, D. Nettleton, and J.M. Reecy. 2006. Transcriptional profiling of myostatin-knockout mice implicates Wnt signaling in postnatal skeletal muscle growth and hypertrophy. FASEB J. published Jan 19, 2006, doi:10.1096/fj.05-5125fje.

Vita: Click here to download

Website: James Reecy

*Peter Reilly

Education: Ph.D., Pennsylvania, 1964

Research Interests:

• Macromolecular Structure and Function--Enzyme-substrate docking, molecular mechanics and molecular dynamics, computed sugar conformations.

Description: Peter Reilly works in biochemical engineering, and more specifically in determining structures and evolutionary patterns of primitive hydrolases, in determining optimal sugar structures by computational molecular mechanics, in computationally docking oligosaccharides into hydrolase active sites to understand their mechanisms, and in using liquid and gas chromatography and mass spectroscopy to identify and quantitate components of agricultural and food processing residues.

Selected Publications:

• Mulakala, C., W. Nerinckx, and P. J. Reilly. The Fate of b-D-Mannopyranose after Its Formation By Endoplasmic Reticulum a-(1 -> 2)-Mannosidase I Catalysis. Carbohydr. Res., 342, 163 (2007).
• Hill, A. D., and P. J. Reilly. Puckering Coordinates of Monocyclic Rings by Triangular Decomposition. J. Chem. Informat. Model., 47, 1031 (2007).
• Mulakala, C., W. Nerinckx, and P. J. Reilly. Docking Studies on Glycoside Hydrolase Family 47 Endoplasmic Reticulum a -(1 -> 2)-Mannosidase I to Elucidate the Pathway to the Substrate Transition State. Carbohydr. Res., 341, 2233 (2006).

Vita: Click here to download

Website: Peter Reilly

Steve Rodermel

Associate BCB Faculty Member

Education: Ph.D., Harvard, 1986

Research Interests: Organelle genetics, chloroplast biogenesis

• Functional and Structural Genomics--Molecular genetics of chloroplasts and regulation of chloroplast biogenesis; proteomics of plant organelles

Description:

Selected Publications:

• Baerr, J.N., J.D. Thomas, B.G. Taylor, S.R. Rodermel and G.R. Gray. 2005. Differential
  photosynthetic compensatory mechanisms exist in the immutans mutant of
  Arabidopsis thaliana. Physiologia Plantarum 124: 390-402. (Cover Article).
• Yu, F., S. Park and S.R. Rodermel. 2005. Functional redundancy of AtFtsH
  metalloproteases in thylakoid membrane complexes. Plant Physiol. 138: 1957-
  1966.
• Alsheikh, M., and S. Rodermel. 2005. Genetics and genomics of chloroplast biogenesis.
  Maydica 50: 443-449. (Invited review: 50th anniversary of Maydica).
• Fu, A., S. Park and S. Rodermel. 2005. Sequences required for the activity of PTOX
  (IMMUTANS), a plastid terminal oxidase: in vitro and in planta mutagenesis of
  iron-binding sites and a conserved sequence that corresponds to Exon 8. J.
  Biol. Chem. 280: 42489-42496. (Cover Article).
• Aluru, M.R., F. Yu, A. Fu and S. Rodermel. 2006. Arabidopsis variegation mutants: new
  insights into chloroplast biogenesis. J. Experimental Botany 57: 1871-1881.
• Rosso, D., A.G. Ivanov, A. Fu, J. Geisler-Lee, L. Hendrickson, M. Geisler, G. Stewart,
  M. Krol, V. Hurry, S.R. Rodermel, D.P. Maxwell and N.P.A. Hüner. 2006.
  IMMUTANS does not act as a stress-induced safety valve in the protection of
  the photosynthetic apparatus of Arabidopsis during steady state photosynthesis.
  Plant Physiol. 142: 574-585.
• Aluru, M.R., D.J. Stessman, M.H. Spalding and S.R. Rodermel. 2007. Alterations in
  photosynthesis in Arabidopsis lacking IMMUTANS, a chloroplast terminal
  oxidase. Photosynthesis Research 91: 11-23.
• Yu, F., A. Fu, M. Aluru, S. Park, Y. Xu, H. Liu, X. Liu, A. Foudree, M. Nambogga and S.
  Rodermel. 2007. Variegation mutants and mechanisms of chloroplast
  biogenesis. Plant Cell & Environment 30: 350-365. (Refereed review)
• Varbanova, M., S. Yamaguchi, Y. Yang, K. McKelvey, A. Hanada, R. Borochov, F. Yu,
  Y. Jikumaru, J. Ross, D. Cortes, C.-J. Ma, J. P. Noel, L. Mander, V. Shulaev, Y.
  Kamiya, S. Rodermel, D. Weiss and E. Pichersky. 2007. Methylation of
  gibberellins by Arabidopsis GAMT1 and GAMT2. Plant Cell 19: 32-45.
• Lee, E.K., D. Cook, H. Hofmann, M. Aluru and S. Rodermel. 2007. The ProbeR Package
  (software) http://cran.r-project.org/doc/packages/ProbeR.pdf
• Taber, H. G., P. Perkins-Veazie, S. Li, W. White, S. Rodermel and Y. Xu. 2008.
  Enhancement of tomato fruit lycopene by potassium is cultivar dependent.
  HortScience 43: 159-165.
• Yu, F., X. Liu, M. Alsheikh, S. Park and S. Rodermel. 2008. Mutations in
  SUPPRESSOR OF VARIEGATION1, a factor required for normal chloroplast
  translation, suppress var2-mediated leaf variegation in Arabidopsis. Plant Cell
  20: 1786-1804.
• Aluru, M., Y. Xu, R. Guo, Z. Wang, S. Li, W. White, K. Wang and S. Rodermel. 2008.
  Generation of transgenic maize with enhanced provitamin A content. J.
  Experimental Botany (in press).
• Fu, A., F. Yu and S. Rodermel. 2008. Translocation of a mitochondrial protein to the
  chloroplast: functional substitution of PTOX by AOX. Proc. Natl. Acad. Sci.
  (in press).

Website: Steve Rodermel

Max Rothschild

Associate BCB Faculty Member

Education: Ph.D., Cornell, 1978

Research Interests: Comparative genomics, for prediction of gene structure, genetic dissection of complex traits. Discovery of genes controlling traits of economic interest in the pig, dog and shrimp

• Functional and Structural Genomics--Comparative genomics and gene discovery; analysis of QTL data, large scale SNP discovery and association analysis  of genes controlling traits of economic interest in the pig, dog and shrimp

Selected Publications:

• Hart, E.A., M. Caccamo, J.L. Harrow, S. Humphray, J. G.R. Gilbert, S. Trevanion, T. Hubbard, J. Rogers and M.F. Rothschild. 2007. Lessons learned from the initial sequencing of the pig genome: comparative analysis of an 8 MB region of pig chromosome 17. Genome Biology 8: R168.
• Rothschild, M.F., Z.H. Hu and Z. Jiang. 2007. Advances in QTL mapping in pigs. Int. J. Biol. Sci. 3: 192-197.
• Rothschild, M.F. and G.S. Plastow. 2008. Impact of genomics in animal agriculture and opportunities for animal health. Trends in Biotechnology. 26:21-25.
• Do, K., S Moon, Z Hu, BH Choi, BW Cho, M F Rothschild, H Kim and  KS Kim.  2008. Development and characterization of in silico SNP map in pigs. Animal Genetics, in press

Vita: Click here to download

Website: Max Rothschild

Donald Sakaguchi

Associate BCB Faculty Member

Education: Ph.D. State University of New York, Albany, 1984

Research Interests: Developmental neurobiology, stem cell biology, development and regeneration of vertebrate visual systems, glaucoma and other retinal diseases, cellular and molecular basis of neuron/glial cell interactions

• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking-- Developmental neurobiology, stem cell transplantation, development and regeneration of vertebrate visual systems, glaucoma and other retinal diseases, coupled biological and mathematical modeling of neural stem cell pattern formation

Description:

Selected Publications:

• Grozdanic, S.D., Ast, A.M., Lazic, T., Kwon, Y.H., Kardon, R.H., Betts, D.M., Sonea, I.M. and Sakaguchi, D.S. (2006) Morphological integration and functional assessment of transplanted neural progenitor cells in healthy and acute ischemic rat eyes. Experimental Eye Research. 82 (4): 597-607.
• Ostojic, J., Sakaguchi, D.S., de Lathouder, Y., Hargrove, M.S., Trent, J.T. III., Kwon, Y.H., Kardon, R.H., Kuehn, M.H., Betts, D.M., and Grozdanic, S.D. (2006) Neuroglobin and Cytoglobin: Oxygen binding proteins in retinal neurons. Investigative Ophthalmology and Visual Science. 47(3): 1016-1023.
• Recknor, J.B., Sakaguchi, D.S., Mallapragada, S.K. (2006) Directed growth and selective differentiation of neural progenitor cells on micropatterned polymer substrates. Biomaterials. 27(22): 4098-4108.
• Eucher, J.N., Uemura, E., Sakaguchi, D.S., and Greenlee, M.H.W. (2007) Amyloid-beta peptide affects mitochondrial function but not differentiation of embryonic and adult rat hippocampal progenitor cells. Experimental Neurology. 203(2):486-92.

Vita: Click here to download

Website: Donald Sakaguchi

*Patrick Schnable

Education: Ph.D., Iowa State, 1986

Research Interests: Plant genomics and bioinformatics

• Bioinformatics
• Functional and Structural Genomics-- structural and functional genomics; mechanisms responsible for heterosis, gene duplication, meiotic recombination, epigenetic phenomena, and carbon sequestration.

Description:

Selected Publications:

• Kalyanaraman A, SJ Emrich, PS Schnable, S Aluru (2007) Assembling genomes on large-scale parallel computers. Journal of Parallel and Distributed Computing, 67: 1240-1255.
• Zhang X, S Medi, LA Borsuk, DS Nettleton, B Buckner, D Janick-Buckner, J Beck, M Timmermans, PS Schnable, MJ Scanlon (2007) Laser microdissection of narrow sheath mutant maize uncovers novel gene expression in the shoot apical meristem. PLoS Genetics, 3(6): 1040-1052.
• Emrich SJ, L Li, TJ Wen, MD Yandeau-Nelson, Y Fu, L Guo, HH Chou, S Aluru, DA Ashlock, PS Schnable (2007) Nearly identical paralogs (NIPs) and implications for maize genome evolution. Genetics, 175(1): 429-439.
• Ohtsu K, M Smith, SJ Emrich, LA Borsuk, R Zhou, T Chen, X Zhang, M Timmermans, J Beck, B Buckner, D Janick-Buckner, D Nettleton, MJ Scanlon, PS Schnable (2007) Global gene expression analysis of the shoot apical meristem of maize (Zea mays L.).  Plant J, 52(3):391-404.
• Barbazuk WB, SJ Emrich, HD Chen, PS Schnable (2007) SNP discovery via 454 transcriptome sequencing.  Plant J, 51: 910-918.
• Emrich SJ, WB Barbazuk, L Li, PS Schnable (2007) Gene discovery and annotation using LCM-454 transcriptome sequencing.  Genome Research, 17: 69-73.
• Swanson-Wagner R, Y Jia, R DeCook, LA Borsuk, D Nettleton, PS Schnable (2006) All possible modes of gene action are observed in a global comparison of gene expression in a maize F1 hybrid and its inbred parents. Proc Natl Acad Sci,103(18): 6805-6810.
• Fu Y, SJ Emrich, L Guo, TJ Wen, S Aluru, DA Ashlock, PS Schnable (2005) Quality assessment of maize assembled genomic islands (MAGIs) and experimental verification of predicted novel genes. Proceedings Natl Acad Sci, 102:12282-12287.

Vita: Click here to download

Website: Patrick Schnable

Taner Sen

Associate BCB Faculty Member

Education: Ph.D., University of Akron, 2003.

Research Interests: Maize bioinformatics, protein structure prediction, protein binding, biological networks.

Description: Analysis, interpretation, and representation of maize sequence as part of MaizeGDB; protein sequence and structure-based methods to understand function as part of the elaborate networks of cellular interactions; protein modeling and dynamics to elucidate structure-function relationships; development and improvement of secondary and tertiary structure prediction methods; protein-protein binding site predictions; structural and functional interpretations of protein-protein interaction networks.

Selected Publications:

• Lawrence, C. J., Harper, L.C., Schaeffer, M.L., Sen, T.Z., Seigfried, T.E., Campell, D.A., “MaizeGDB: the Maize Model Organism Database for Basic, Translational, and Applied Research”, International Journal of Plant Genomics, in press.

• Sen, T.Z., Kloster, M., Kloczkowski, A., Kolinski, A., Bujnicki, J.M., Jernigan, R.L., “Structure prediction and normal mode analysis of the outer membrane transporter FecA”, Biophysical Journal, 94(7), 2482–2491, 2008.

• Sulkowska, J.I., Kloczkowski, A., Sen, T.Z., Cieplak, M., Jernigan, R.L. “Predicting the order in which contacts are broken during single molecule protein stretching experiments”, Proteins, 71, 45-60, 2008.
• Cheng, H., Sen, T.Z., Jernigan, R.L., Kloczkowski, A., “Consensus Data Mining (CDM) Protein Secondary Structure Prediction Server: Combining GOR V and Fragment Database Mining (FDM)”, Bioinformatics, 23(19), 2628-2630, 2007.
• Peto, M., Sen, T.Z., Jernigan, R.L., Kloczkowski, A., “Generation and enumeration of compact conformations on the 2D triangular and 3D fcc lattices”, Journal of Chemical Physics, 127(4):044101, 2007.

Vita: Click here to download

Website: Taner Z. Sen

Jacqueline Shanks

Associate BCB Faculty Member

Education: Ph.D.,California Institute of Technology, 1989

Research Interests: Biochemical engineering, metabolic engineering of plant secondary metabolites, NMR for metabolic evaluation of in vivo fluxes, phytoremediation

• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking-- Experimental and mathematical approaches to metabolic flux analysis in plants; plant metabolic engineering

Description:

Selected Publications:

• Sriram, G., D. B. Fulton, V. Iyer, J. M. Peterson, R. Zhou, M. E. Westgate, M. H. Spalding and J. V. Shanks. 2004. Quantification of Compartmented Metabolic Fluxes in Developing Soybean (Glycine max) Embryos by Employing Biosynthetically Directed Fractional 13C Labeling, 2-D [ 13C,  1H] NMR and Comprehensive Isotopomer Balancing. Plant Physiol.136: 3043-3057
• Sriram, G. and J. V. Shanks. 2004. Improvements in Metabolic Flux Analysis using Carbon Bond Labeling Experiments: Bondomer Balancing and Boolean Function Mapping. Metabol. Eng, 6, 116-132.
• Morgan, J., and J.V. Shanks. 2002. Metabolic flux analysis of plant secondary metabolism using a biogenetic organizational approach. Metabolic Engr. 4, 257-262.
• Shanks, J.V. and G. Stephanopoulos. 2000. Biochemical Engineering: bridging the gap between gene and product. Current Opinion in Biotechnology11, 169-70.

Vita: Click here to download

Website: Jacqueline Shanks

Michael Smiley

Associate BCB Faculty Member

Education: Ph.D., Michigan, 1980

Research Interests:

• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking

Selected Publications:

• Smiley, M.W., A monotone conservative Eulerian-Lagrangian scheme for reaction-diffusion-convection equations modeling chemotaxis, Numerical Methods for Partial Differential Equations, Vol. 23, (2007), pp. 553-586. Published online: March 22, 2007.
• Smiley, M.W., H.A. Levine, M. Nilsen-Hamilton, and A. Tucker, A mathematical model for the onset of avascular tumor growth in response to the loss of P53 function, Cancer Informatics -- 2006 Edition (this is electronic journal published by Libertas Academica and can be accessed from the web page http://la-press.com/).

Website: Michael Smiley

*Jonathan Smith

Associate BCB Faculty Member

Education: Ph.D., Cambridge, 1975

Research Interests: Combinatorics and information theory, modeling of complex systems, mathematical biology

• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking-- Combinatorics and information theory; modelling of complex systems; mathematical biology

Description: As a model for the use of top-down, information-theoretic techniques for handling data describing the evolution of complex systems, the intensive demographic state of a human population has been reduced from the full Leslie matrix description to a single five-dimensional parameter vector. The next stage in the development of this technique involves an analysis of the long-term kinematics of the parameter vector for a given population. It is proposed to use the data for Sweden, which are of high quality and trace back several hundred years. Understanding the kinematics is a preliminary to the development of a dynamics, which should then provide more reliable long-term demographic projections than those obtained from the ergodic theory of Leslie matrices.

Selected Publications:

• Patterns of information storage and senescence, in "Proceedings of FIS2005, The Third Conference on the Foundations of Information Science, Paris, July 4-7, 2005" (ed. M. Petitjean), Electronic Edition, ISBN 3-906980-17-0.
• A macroscopic approach to demography, J. Math. Biol. 48 (2004), 105-118.

Vita: Click here to download

Website: Jonathan Smith

*Guang Song

Education: Ph.D., Computer Science, Texas A&M University, 2003

Research Interests: Protein Structure and Dynamics; Protein Folding Pathways, Energy Landscape, and Kinetics; Ligand Migration Pathways; Ligand Binding; Structure-Function Studies of Biophysical Processes; Computer Modeling and Simulation; Motion Planning

Description:

Selected Publications:

• Guang Song and Robert L. Jernigan, "vGNM: a Better Model for Understanding the Dynamics of Proteins in Crystals" Journal of Molecular Biology, 2007, to appear.
• Lei Yang, Guang Song, and Robert L. Jernigan, "How Well Can We Understand Large-Scale Protein Motions Using Normal Modes of Elastic Network Models?" Biophysical Journal, 2007, to appear.
• Guang Song and Robert L. Jernigan, "An Enhanced Elastic Network Model to Represent the Motions of Domain-Swapped Proteins," Proteins, 63(1):197-209, 2006.
• Guang Song and Nancy M. Amato, "A Motion Planning Approach to Folding: From Paper Craft to Protein Folding, " IEEE Transactions on Robotics and Automation, 20(1):60-71, 2004.
• Nancy M. Amato, Ken A. Dill, and Guang Song, "Using Motion Planning to Map Protein Folding Landscapes and Analyze Folding Kinetics of Known Native Structures," Journal of Computational Biology, 10(3-4):239-256, 2003. Featuring selected papers from RECOMB 2002.
• Guang Song and Nancy M. Amato, "Using Motion Planning to Study Protein Folding Path-ways," in Proceedings the 5th ACM International Conference on Computational Molecular Biology (RECOMB), pp. 287-296, April 2001, Montreal, Canada.

Vita: Click here to download

Website: Guang Song

*Xueyu Song

Education: Ph.D., Caltech, 1995

Research Interests: Theory of protein crystallization, protein-protein/RNA interactions

• Bioinformatics-- Three-dimensional atomic structures of proteins form the foundation of our molecular understanding of biology. X-ray crystallography is the major and sometimes only tool for the determination of these detailed protein structures. The bottleneck of this method is to grow a large and good quality crystal used in diffraction. For membrane proteins which carry out some of the most fundamental processes in biology such as photosynthesis, vision and nerve communications, it is exceedingly difficult to find the optimal crystallization conditions because of their peculiar molecular properties. This difficulty is in no small part due to the lack of a transparent and reliable theoretical model to describe the crystallization process. Our research goal is to develop such a theoretical model and to explore the physical principles of finding optimal crystallization conditions. By studying the relationship between the crystallization conditions and the physical parameters of the protein solution, we should be able to provide useful guidance to the search for protein crystallization conditions.
• Functional and Structural Genomics-- Same as above

Description:

Selected Publications:

Vita: Click here to download

Website: Xueyu Song

*Alex Travesset

Education: Ph.D., Barcelona, 1997

Research Interests:

• Computational Molecular Biology and Mathematical Biology--Theoretical models and simulations (including all atomic MD) of phospholipids and interactions of phospholipids with proteins. Signaling phospholipids (PIP2). Electrostatic properties of biological systems (theoretical).

Description: The research in my group focuses around two main topics:

1) Properties of phospholipids: What determines the phase diagram of phospholipids and, in particular, the influence of ions in solution. We are particularly interested in phospholipids such as Phophatidic acid and Phosphatidyl-Inositol Bisphosphate, which play a critical role in transducing signals.

2) Self assembly of soft matter systems (polymers, colloids, liquid crystals) and its relation to biological systems.

Selected Publications:

• J. Faraudo and A. Travesset , Phosphatidic Acid Domains in Membranes: effect of Divalent Counterions, Biophys. J.,(in Press)(2007).
• A. Travesset, Effect of dipolar moments in domain sizes of lipid bilayers and monolayers
• J. Chem. Phys. 125 (8), 084905 (2006).
• W. Bu, D. Vaknin, and A. Travesset, How Accurate Is Poisson-Boltzmann Theory for Monovalent Ions near Highly Charged Interfaces, Langmuir 22, 5673 (2006).
• M. Bowick, D.R. Nelson, and A. Travesset, Curvature-Induced Defect Unbinding in Toroidal vesicles, Phys. Rev. E 69, 41102 (2004).
• Bowick and A. Travesset, The Statistical Mechanics of Membranes, Phys. Rep. 344
  (2001) 255.

Vita: Click here to download

Website: Alex Travesset

Christopher Tuggle

Education: Ph.D., Minnesota, 1986

Research Interests: Functional genomics and systems biology of regulatory pathways controlling inflammation and appetite.

• Functional and Structural Genomics-- Transcriptional profiling to understand pathways controlling reproduction, development, growth and infectious disease. Characterization and prediction of gene regulatory regions. Large-scale gene discovery and mapping (EST sequencing and analysis)

Description: The research in my lab is currently focused on the following porcine functional genomic projects, all of which are externally funded.

1. How the transcriptome of the developing embryo and the uterine endometrium changes during implantation, a critically important stage of successful reproduction.
2. How the transcriptome of the immune system reacts to and controls infection by Salmonella spp., zoonotic pathogens impacting food safety.
3. How the trancriptome of relevant tissues that control feed intake respond to food limitation and selection for decreased food intake.

Selected Publications:

• Tuggle C.K., Y.F. Wang and O. Couture. 2007. INVITED REVIEW: Advances in Swine Transcriptomics. International Journal of Biological Sciences 3:132-152.
• Uthe, J.J., Royaee, A., Lunney, J.K., Stabel, T.J., Zhao, S.-H., Tuggle, C.K., Bearson, S.M.D. 2007. Porcine differential gene expression in response to Salmonella enterica serovars Choleraesuis and Typhimurium. Molecular Immunology 44:2900-2914.
• Wang, Y.F., Qu, L., Uthe, J.J., Bearson, S.M.D., Kuhar, D., Lunney, J.K., Couture, O.P., Nettleton, D., Dekkers, J.C.M., and C. K. Tuggle. 2007. Global Transcriptional Response of Porcine Mesenteric Lymph Nodes to Salmonella enterica serovar Typhimurium. Genomics 90:72-84.
• Tuggle, C.K., Dekkers. J., J. Reecy. 2006. Integration of Structural and Functional Genomics. Animal Genetics 37 (Supp. 1): 1-6.
• Zhao. S.H., D. Kuhar, J. K. Lunney, H. Dawson, C. Guidry, J.J. Uthe, S. M. D. Bearson, J. Recknor, D. Nettleton, C.K. Tuggle. 2006. Gene expression profiling in Salmonella Choleraesuis infected porcine lung using a long oligonucleotide microarray (Mammalian Genome 17:777-89).
• Zhao, S.-H. J. Recknor, J.K. Lunney, D. Nettleton, D. Kuhar, S. Orley, H. Dawson, C. K Tuggle. 2005. Validating a first-generation porcine oligonucleotide microarray for transcriptional profiling in the pig. Genomics 86:618-625.
• Abbott, M.A., and C.K. Tuggle. 2005. Ectopic HOXA5 expression results in abnormal differentiation, migration and p53-independent cell death of superficial dorsal horn neurons. Brain Res. Dev. Brain Res. 159:87-97.
• Caetano, A.R., Edeal, J.B., Burns, K., Johnson, R.K., C.K. Tuggle. Pomp D. 2005. Physical Mapping of Genes in the Porcine Ovarian Transcriptome. Animal Genetics 36:322-330.
• Joksimovic, M., Jeannotte, L., C.K. Tuggle. 2005. Dynamic expression of murine HOXA5 protein in the central nervous system. Mechanisms of Development-Gene Expression Patterns 5: 792-800.
• Tuggle, C.K., J.A. Green, C. Fitzimmons, R. Woods, R.S. Prather, S. Malchenko, M.B. Soares, T. Kucaba, K. Crouch, C. Smith, D. Tack, N. Robinson, B. O'Leary, T. Scheetz, T. Casavant, D. Pomp. J.B. Edeal, Y. Zhang, M.F. Rothschild, K. Garwood, and W. Beavis. 2003. EST-based gene discovery in pig: virtual expression patterns and comparative mapping to human. Mamm. Genome 14:565-579.

Vita: Click here to download

Website: Christopher Tuggle

Nicole Valenzuela

Education: Ph.D., SUNY at Stony Brook, 1999

Research Interest: Evolutionary and functional ecogenomics of sex determination

Functional and Structural Genomics-- Evolutionary and ecological functional genomics associated with the development of the sexual phenotype. Modeling evolution of sex determination. Thermal sexual polyphenisms in vertebrates. Gene discovery. Comparative gene expression. Chromosome evolution.

Research Interest: Evolutionary and functional ecogenomics of sex determination

• Functional and Structural Genomics-- Evolutionary and ecological functional genomics associated with the development of the sexual phenotype. Modeling evolution of sex determination. Thermal sexual polyphenisms in vertebrates. Gene discovery. Comparative gene expression. Chromosome evolution.
• Genome Evolution­-Evolution of gene networks underlying sexual development. Molecular evolution. Chromosome evolution. Description:

Description:

• Martinez, P., Ezaz T., Valenzuela, N., Georges, A., and Graves J.A.M. 2008. An XX/XY heteromorphic sex chromosome system in the Australian chelid turtle Emydura macquarii, a new piece in the puzzle of sex chromosome evolution in turtles. Chromosome Research (DOI: 10.1007/s10577-008-1228-4).
• Valenzuela, N. 2008. Sexual development and the evolution of sex determination. Sexual Development 2(2): 64-72.
• Valenzuela, N. 2008. Evolution of the gene network underlying gonadogenesis in turtles with temperature-dependent and genotypic sex determination. Integrative and Comparative Biology. doi:10.1093/icb/icn031
• Janes D.E., Organ C., and Valenzuela N. 2008. New resources inform study of genome size, content and organization in non-avian reptiles. Integrative and Comparative Biology. doi:10.1093/icb/icn010
• Valenzuela, N. 2008. Relic thermosensitive gene expression in a turtle with genotypic sex determination. Evolution 62-1: 234-240.
• Valenzuela, N. and Shikano T. 2007. Embryological ontogeny of Aromatase gene expression in Chrysemys picta and Apalone mutica turtles: comparative patterns within and across temperature-dependent and genotypic sex-determining mechanisms. Development, Genes and Evolution 217: 5562.
• 25. Valenzuela, N., LeClere A., and Shikano T. 2006. Comparative expression of steroidogenic factor 1 in Chrysemys picta and Apalone mutica turtles with environmental and genotypic sex determination. Evolution and Development 8 (5): 424-432.
• Ezaz T., Valenzuela, N., Gruetzner F., Miura I., Burke R., Georges, A. and Graves J.M. 2006. Cryptic XY sex chromosome system in a GSD turtle, Chelodina longicollis (Chelidae, Reptilia). Chromosome Research  14:139-150.
• Devon E. Pearse, A.D. Arndt, N.Valenzuela, B.A. Miller, V. Cantarelli, J.W. Sites, Jr. 2006. Estimating population structure under non-equilibrium conditions in a conservation context: Continent-wide population genetics of the giant Amazon river turtle Podocnemis expansa (Chelonia; Podocnemidae). Molecular Ecology 15: 985-1006.
• Valenzuela, N. and V. Lance, Eds. 2004. Temperature Dependent Sex Determination in Vertebrates. Smithsonian Books. Washington D.C.
• Valenzuela, N., D.C. Adams, and F.J. Janzen. 2003. Pattern does not equal process: Exactly when is sex environmentally determined? American Naturalist 161 (4): 676-683.

Vita: Click here to download

Website: Nicole Valenzuela

Jonathan F. Wendel

Associate BCB Faculty Member

Education: Ph.D., North Carolina, 1983

Research Interests:

• Genome Evolution-- Phylogenetics and molecular evolution, particularly in plants, with a special focus on the evolution of duplicated genes and genomes

Selected Publications:

• Grover, C. E., H. Kim, R. A. Wing, A. H. Paterson, and J. F. Wendel. 2007. Microcolinearity and genome size evolution in the AdhA region of diploid and polyploid cotton (Gossypium). The Plant Journal (in press).
• Udall, J. A., F. Cheung, A. W. Woodward, J. M. Swanson, L. Flagel, R. Hovav, R. A. Rapp, D. Nettleton, J. J. Lee, A. R. Gingle, C. Town, Z. J. Chen, and J. F. Wendel. 2007. Spotted cotton oligonucleotide microarrays for gene expression analysis. BMC Genomics (in press).
• Fortune, P. M., K. A. Schierenbeck, A. K. Ainouche, J. Jacquemin, J. F. Wendel, and M.L. Ainouche. 2007. Evolutionary dynamics of Waxy and the origin of hexaploid Spartina species (Poaceae). Molecular Phylogenetics and Evolution (in press).
• Adams, K. L. and J. F. Wendel. 2006. Allele-specific, bi-directional silencing of an alcohol dehydrogenase gene in different organs of interspecific cotton hybrids. Genetics 17: 2139-2142.
• Udall, J. A., J. Swanson, K. Haller, R.A. Rapp, M. Sparks, J. Hatfield, Y. Yu, Y. Wu, A.B. Arpat, B.A. Sickler, T.A. Wilkins, J.-Y. Guo, X.-Y. Chen, E. Taliercio, R. Turley, C. Dowd, H. McFadden, N. Klueva, P. Payton, R. Allen, D. Zhang, C. Haigler, C. Wilkerson, J. Suo, S.R. Schulze, M.L. Pierce, M. Essenberg, H. Kim, D.J. Llewellyn, E.S. Dennis, D. Kudrna, R. Wing, A.H. Paterson, C. Soderlund, and J.F. Wendel. 2006. A global assembly of cotton ESTs. Genome Research 16: 441-450.
• Álvarez, I. and J. F. Wendel. 2006. Ancient interspecific introgression and modern genetic differentiation within Gossypium aridum (Malvaceae) and its relatives. Evolution 60: 505-517.
• Udall, J. A., J. M. Swanson, D. Nettleton, R. J. Percifield, and J. F. Wendel. 2006. A novel approach for characterizing expression levels of genes duplicated by polyploidy. Genetics 173: 1823-1827.
• Keyte, A. L., R. Percifield, B. Liu, and J. F. Wendel. 2006. Infraspecific DNA methylation polymorphism in cotton (Gossypium hirsutum L.). Journal of Heredity 97: 444-450.
• Hawkins, J. S., H. Kim, J. D. Nason, R. A. Wing, and J. F. Wendel. 2006. Differential lineage-specific amplification of transposable elements is responsible for genome size variation in Gossypium. Genome Research 16: 1252-1261.
• Udall, J. A. and J. F. Wendel. 2006. Polyploidy and crop improvement. The Plant Genome, a Supplement to Crop Science 46: S3-14.
• Adams, K. L. and J. F. Wendel. 2005. Novel patterns of gene expression in polyploid plants. Trends in Genetics 21: 539-543. Rapp, R. and J. F. Wendel. 2005. Epigenetics and plant evolution. New Phytologist 168: 81-91.

Vita: Click here to download

Website: Jonathan F. Wendel

*Steve Whitham

Associate BCB Faculty Member

Education: Ph.D., Univ. of CA, Berkeley, 1995

Research Interests:

• My research program involves the functional genomic analysis of plant microbe interactions, and we have three major projects that would be suitable for a bioinformatics student. First, we have employed DNA microarrays to analyze the responses of plants to microbes and are now using these data to test the functions of genes that we hypothesize may be involved in disease defense networks. Second, we are developing high throughput methods to analyze gene functions in soybean using a technique called virus induced gene silencing. Third, we are preparing to do sequencing of the Asian soybean rust haustoria transcriptome using the 454 technology from Roche. I believe that the data sets that are available and the three complementary projects that are in progress in our lab present some excellent opportunities for research projects for a student in the BCB program. I am able to provide financial support for a graduate research assistantship through existing grant funds.

Selected Publications:

• Tasma, I. M., Brendel, V., Whitham, S. A., and Bhattacharyya, M. K.* (2008). Expression and
  evolution of the phosphoinositide-specific phospholipase C gene family in Arabidopsis thaliana.
  Plant Physiol. Biochem. 46(7):627-37. doi:10.1016/j.plaphy.2008.04.015
• Shiboleth, Y. M., Haronsky, E., Leibman, D., Arazi, T., Wassenegger, M., Whitham, S. A.,
  Gaba, V., and Gal-On., A.* (2007). The conserved FRNK box in plant viral suppressor of gene
  silencing HC-Pro is required for small RNA binding and mediates symptom development. J.
  Virol. 81:13135-13148. doi: 10.1128/JVI.01031-07
• van de Mortel, M., Recknor, J. C., Graham, M. A., Nettleton, D., Dittman, J. D., Nelson, R. T.,
  Godoy, C. V., Abdelnoor, R. V., Almeida, A. M. R., Baum, T. J.* and Whitham, S. A.* (2007).
  Distinct biphasic mRNA changes in response to Asian soybean rust infection. Mol. Plant
  Microbe Interact. 20:887-899. doi: 10.1094/MPMI-20-8-0887
• Wise, R. P.*, Moscou, M. J., Bogdanove, A. J., Whitham, S. A. (2007). Transcript profiling in
  host–pathogen interactions. Annu. Rev. Phytopathol. 45:329-369.doi:10.1146/annurev.phyto.45.011107.143944
• Yang, C., Guo, R., Jie, F., Nettleton, D., Peng, J., Carr, T., Yeakley, J. M., Fan, J.-B., Whitham,
  S. A.* (2007). Spatial and temporal analysis of Arabidopsis thaliana gene expression in
  response to Turnip mosaic virus infection. Mol. Plant Microbe Interact. 20:358-370. doi:
  10.1094/MPMI-20-4-0358

Vita: Click here to download

Website: Steve Whitham

Stephen Willson

Associate BCB Faculty Member

Education: Ph.D., Michigan, 1973

Research Interests: Reconstruction of phylogenetic trees, supertrees, and networks.

• Genome Evolution--Reconstruction of phylogenetic trees, networks, and supertrees from data, especially involving distance estimates.

Description: I study methods for analyzing phylogeny. I develop algorithms for constructing phylogenetic trees and networks from data, and I prove theorems about the methods. Of special interest are methods that give signals for hybridization or lateral gene transfer and methods such as supertrees to combine phylogenetic information from different researchers.

Selected Publications:

• Willson, S. Unique determination of some homoplasies at hybridization events.   Bulletin of Mathematical Biology  69 (2007) 1709-1725.
• Willson, S.  Reconstruction of some hybrid phylogenetic networks with homoplasies from distances.  Bulletin of Mathematical Biology 69 (2007) 2561-2590.
• Willson, S. Unique reconstruction of tree-like phylogenetic networks from distances between leaves. Bulletin of Mathematical Biology 68 (2006) 919-944.
• Willson, S. Unique solvability of certain hybrid networks from their distances. Annals of Combinatorics 10 (2006) 165-178.
• Willson, S. Consistent formulas for estimating the total lengths of trees. Discrete Applied Mathematics 148 (2005) 214-239.
• Willson, S. Minimum evolution using ordinary least-squares is less robust than neighbor-joining. Bulletin of Mathematical Biology 67 (2005) 261-279.
• Willson, S. Constructing rooted supertrees using distances, Bulletin of Mathematical Biology 66 no 6 (2004): 1755-1783.

Vita: Click here to download

Website: Stephen Willson

*Roger Wise

Education: Ph.D., Michigan State, 1983

Research Interests: Molecular signaling and parallel expression analysis in host-pathogen interactions

• Bioinformatics- - Large-scale genetical genomics and parallel expression profiling
• Functional and Structural Genomics-- Functional analysis of agronomically important genes selected through analysis of GeneChip profiling experiments
• Genome Evolution-- automated annotation of complex LTR retrotransposons and repeated regions in maize and other cereals, nuclear-mitochondrial interactions.

Description:

Dissection of coexpression networks in barley-powdery mildew interactions: a multi-dimensional approach to understanding parasitism by obligate biotrophs

Regulation of gene expression in barley-powdery mildew interactions influences the establishment of fungal biotrophy and the development of host resistance. To identify global expression responses to the powdery mildew fungus, Blumeria graminis f. sp. hordei, 468 Barley1 GeneChips were used to profile the expression of 21,439 genes in inoculated vs. non-inoculated seedlings at hours 0, 8, 16, 20, 24, and 32 for each of nine variants of genes in the Mla resistance signaling pathway, as well as mutants programmed cell death ( NSF Plant Genome Award #0500461 ). We are analyzing these data to build coexpression networks containing genes involved in sugar transport, photosynthesis, WRKY signaling, secretion of PR proteins, signal peptide processing, and abiotic stress signaling. Single cell dsRNAi (TIGS), Virus Induced Gene Silencing (VIGS), transcript based cloning, and proteomics experiments are being used to dissect the various sub-networks and time-course interactions of disease defense pathways.

Selected Publications:

• Kronmiller, BA and RP Wise. 2008. TEnest: Automated chronological annotation and visualization of maize nested transposable elements. Plant Physiology: 45-59 . [Cover article]
• Wise, RP, M Moscou, SA Whitham, AJ Bogdanove. 2007. Transcript Profiling in Host – Pathogen Interactions. Annual Review of Phytopathology 45: 329-369.
• Potokina, E, A Druka, ZW Luo, R Wise, R Waugh, and MJ Kearsey. 2007. eQTL analysis of 16,000 barley genes reveals a complex pattern of genome wide transcriptional regulation. Plant Journal: 53(1): 90-101.
• Wise, RP, RA Caldo +, L Hong +, L Shen, JA Dickerson. 2007. BarleyBase/PLEXdb: A Unified Expression Profiling Database for Plants and Plant Pathogens. Pages 347-363 In Methods in Molecular Biology, Vol. 406, Plant Bioinformatics - Methods and Protocols. Edwards, D. ed. Humana Press, Totowa, NJ. 2007.
• Caldo RA, D Nettleton, J Peng, and RP Wise. 2006. Stage-specific suppression of basal defense discriminates barley plants containing fast- and delayed-acting Mla powdery mildew resistance alleles. Molecular Plant-Microbe Interactions 19(9): 939-947.
• Druka, A, G Muehlbauer, I Druka, R Caldo, U Baumann, N Rostoks, A Schreiber, R Wise, T Close, A Kleinhofs, A Graner, A Schulman, P Langridge, K Sato, P Hayes, J McNicol, D Marshall and R Waugh. 2006. An atlas of gene expression from seed to seed through barley development. Functional and Integrative Genomics 6: 202-211.

Vita: Click here to download

Website: Roger Wise

*Zhijun Wu

Education: Ph.D., Rice, 1991

Research Interests: Biomolecular and biosystems modeling and simulation, numerical linear algebra, nonlinear optimization, linear programming, integer and combinatorial optimization, numerical solution of ordinary and partial differential equations, parallel high-performance computing

• Bioinformatics--

  Molecular distance geometry, protein structure refinement, simulation of transition of protein conformation, constrained molecular dynamics, potential energy minimization, protein geometry databases, multiscale protein modeling, metabolic network simulation and optimization

• Macromolecular Structure and Function--Same as above
• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking--Same as above

Description:

Selected Publications:

• A Penalty-Function Method for Constrained Molecular Dynamics Simulation, to appear in Numerical Analysis and Modeling, 2008 (with Ajith Gunaratne).
• A Multiple Shooting Algorithm for Solving the Boundary Value Problems in Molecular Dynamics Simulation, to appear in Numerical Analysis and Modeling, 2008 (with Peter Vedell).
• Enhancement of Torsion Angle Constraints in NMR Structure Refinement via Database Derived Distance Constraints, Journal of Bioinformatics and Computational Biology, Vol 6, No. 2, 2008, pp. 283-300 (with Feng Cui and Robert Jernigan).
• Generating Rigid Protein Structures with Sparse Sets of Inter-Atomic and Inter-Residual Distances, Optimization Letters, Vol 2, No. 3, 2008, pp. 319- 331 (with Di Wu and Yaxiang Yuan).
• PRTAD: A Protein Residue Torsion Angle Distribution Database, Proceedings of IEEE International Conference on Bioinformatics and Biomedicine, 2007, pp. 24-31 (with Xiaoyong Sun, Di Wu, and Robert Jernigan).
• Improvement of Under-Determined Loop Regions of Human Prion Protein by Database Derived Distance Constraints, Proceedings of IEEE International Conference on Bioinformatics and Biomedicine, 2007, pp. 14-23 (with Feng Cui,
  Kriti Mukhopadhyay, Wonbin Young, and Robert Jernigan).
• Refinement of NMR-Determined Protein Structures with Database Derived Mean Force Potentials, Proteins: Structure, Function, Bioinformatics, Vol. 68, 2007, pp. 232-242 (with Di Wu and Robert Jernigan).
• PIDD: A Protein Inter-atomic Distance Distribution Database, Journal of Nucleic Acid Research, Vol. 35, 2007, pp. D202-D207 (with Di Wu, Feng Cui, and Robert Jernigan).

Vita: Click here to download

Website: Zhijun Wu

*Eve Wurtele

Education: Ph.D., UCLA, 1980

Research Interests: Metabolic networking of acetyl-CoA starch in plants, computational biology

• Functional and Structural Genomics-- Metabolic networking in plants; evolution of biotin-containing enzymes; RNA and protein profiling analyses
• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking--Same as above

Description: Plants can be considered “environmentally clean”, solar-powered factories that produce a wide range of chemicals from simple precursors (carbon dioxide, nitrogen, sulfur, etc.). These complex plant-derived chemicals include carbohydrates, proteins, oils, and vitamins, and have nutritional, industrial, and medicinal uses. The metabolic processes that biosynthesize these complex molecules are responsive to growth and developmental signals determined by the genetic blueprint of the organism as it adapts to the ever-changing environmental stimuli. These metabolic processes are the chemical basis for life. My research, juxtaposed at the interface between biology and computational sciences, centers on this interplay between the metabolic and regulatory signals: the metabolic network of plants. My foci are 1) the development of software to explore the metabolic and regulatory network in conjunction with experimental data from millions of datapoints (http://metnet.vrac.iastate.edu/), and 2) the elucidation of the metabolic networks associated with the two-carbon activated molecule, acetyl-CoA.

Selected Publications:

• Fatland B, Nikolau BJ, Wurtele ES. 2005. Reverse Genetic Characterization of Cytosolic Acetyl-CoA Generation by ATP-citrate lyase in Arabidopsis. Plant Cell. 2005 Jan; 17(1):182-203. Epub 2004 Dec 17.
• Jenkins H, Hardy N, Beckmann M, Draper J, Smith AR, Taylor J, Fiehn O, Goodacre R, Raoul Bino R, Hall R, Kopka J, Lange BM, Liu JR, Mendes P, Nikolau BJ, Oliver SG, Paton NW, Roessner-Tunali U, Saito K, Smedsgaard J, Sumner LW, Wurtele ES, Kell DB. 2005. A proposed framework for the description of plant metabolomics experiments and their results.  Nature Biotech 22 (January Issue).
• J. A. Dickerson, P. Du, E. Wurtele, J. Li. 2004. Fuzzy modeling of metabolic maps in MetNetDB. NAFIPS04.

Link: http://metnet.vrac.iastate.edu/

Vita: Click here to download

Website: Eve Wurtele

*Edward Yu

Associate BCB Faculty Member

Education: Ph.D.,University of Michigan, 1997

Research Interests: Structural and mechanistic aspects of membrane transport; X-ray crystallography of membrane proteins; Biophysics

• Macromolecular Structure and Function-- Structural and mechanistic aspects of membrane transport; X-Ray crystallography of membrane proteins; Biophysics

Description:

Selected Publications:

• Su, C.-C., Long, F., McDermott, G., Shafer, W. M., and Yu, E.W. 2008. Crystallization and
  preliminary X-ray diffraction analysis of the multidrug efflux transporter NorM from Neisseria
  gonorrhoeae. Acta Cryst. F64:289-292.
• Gu, R., Su, C.-C., Shi, F., Li, M., McDermott, G., Zhang, Q., and Yu, E.W. 2007. Crystal
  structure of the transcriptional regulator CmeR from Campylobacter jejuni. J. Mol. Biol. 372:583-
  593.
• Li, M., Gu, R., Su, C.-C., Routh, M., Harris, K.C., Jewell, E.S., McDermott, G., and Yu, E.W.
  2007. Crystal structure of the transcriptional regulator AcrR from Escherichia coli. J. Mol. Biol.
  374:591-603.
• Su, C.-C., and Yu, E.W. 2007. Ligand-transporter interaction in the AcrB multidrug efflux pump
  determined by fluorescence polarization assay. FEBS Lett. 581:4872-4976.
• Su, C.-C., Rutherford, D.J., and Yu, E.W. 2007. Characterization of the multidrug efflux
  regulator AcrR from Escherichia coli. Biochem. Biophys. Res. Comm. 361:85-90.
• Su, C.-C., Li, M., Gu, R., Takatsuka, Y., McDermott, G., Nikaido, H., and Yu, E.W. 2006.
  Conformation of the AcrB Multidrug Efflux Pump in Mutants of the Putative Proton Relay
  Pathway. J. Bacteriol. 188:7290-7296.

Vita: Click here to download

Website: Edward Yu

* Asterisked Faculty currently serve as major or co-major professors for BCB Students.