Website: Adam Bogdanove

Khalid Boushaba

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

Research Interests: Mathematical Biology, Applied Mathematics and Mathematical Modeling, Partial Differential Equations

Vita: Click here to download

Website: Khalid Boushaba

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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:

• 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.
Vita: Click here to download

Website: Volker Brendel

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Anne Bronikowski

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

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Alicia Carriquiry

Education: Ph.D., Iowa State, 1989

Research Interests: Statistical methods in bioinformatics and biological sciences

• Bioinformatics-- Statistical methods in bioinformatics and biological sciences

Description:

Selected Publications:

• Fernandez, S., Fernando, R., and Carriquiry, A.L. 2001. An algorithm to sample marker genotypes in a pedigree with loops. Case Studies in Bayesian Statistics, Vol. V, Gatsonis, C. et al. ( eds.). Lecture Notes in Statistics, Springer- Verlag. 309-328. Papers\Bioinformatics and Biological Statistics\Fernandez- CaseStudies.pdf
• Fernandez, S. A., Fernando, R. L., and Carriquiry, A. L.. 2001. An algorithm to sample unobservable genotypes in complex pedigrees.  ISBA 2000 Proceedings: Bayesian Methods with Applications to Science, Policy, and Official Statistics.  Italy: European Communities Press. 125-135. Papers\Bioinformatics and Biological Statistics\Fernandez- ROS.pdf
• Fernandez, S. A., Fernando, R. L., Guldbrandtsen, B., Stricker, C., Schelling, M., and Carriquiry, A. L. 2002. Irreducibility and efficiency of ESIP to sample marker genotypes in large pedigrees with loops. Genetics, Selection, Evolution. 34:537-555.
• Che, P., Love, T.M., Frame, B.R, Wang, K., Carriquiry, A.L., and Howell, S.P. Gene expression changes during germination and maturation of somatic embryos in maize cultures. Plant Molecular Biology.  In press. Papers\Bioinformatics and Biological Statistics\ PlantMolecBiol.pdf

Vita: Click here to download

Website: Alicia Carriquiry

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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:

• Scott Emrich, Tsui-Jung Wen, Marna Yandeau-Nelson, Yan Fu, Li Li, Ling Guo, Hui-Hsien Chou, Srinivas Aluru, Daniel Ashlock, and Patrick Schnable. 2007. Nearly identical paralogs (NIPs): implications for maize (Zea mays L.) genome evolution. Genetics In press.
• 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.
Vita: Click here to download

Lab Website: Hui-Hsien Chou

Department Website: Hui-Hsien Chou

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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:

• Lee, E.-K., Cook, D., Hofmann, H., Wurtele, E., Kim, D., Kim, J., and An, H. (2004) GeneGobi: Visual Data Analysis Tools for Microarray Data, COMPSTAT '04, Aug 22-27, 2004, Prague, Czech Republic, Pages forthcoming.
• Cook, D., Hofmann, H., Lee, E.-K., Yang, H., Nikolau, B. and Wurtele, E. (2004). Visual Methods For Data From Two Factor Single-Replicate Gene Expression Studies, Technical Report 04-05: http://www.stat.iastate.edu/preprint/articles/2004-05.pdf, Department of Statistics, Iowa State University.
• 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.
• Meyer, D. and Cook, D. (2000). Visualization of Data. Current Opinion in Biotechnology, 11:89--96.

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

Vita: Click here to download

Website: Dianne Cook

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Jennifer Davidson

Education: Ph.D., Florida, 1989

Research Interests: Genetic algorithms, protein structure, computer vision on plants

• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking-- Image processing of gene arrays; optimization techniques - genetic algorithms, simulated annealing; stochastic models for gene translations

Description:

Selected Publications:

Vita: Click here to download

Website: Jennifer Davidson

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Jack Dekker

Education: Ph.D., Michigan State, 1980

Research Interests: Weed seed behavior as a complex adaptive system, formalizing seed behavior computational models

• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking-- Weedy Setaria spp. as a complex adaptive system; formalizing Setaria seed behavior computational models; emergent behavior of Setaria biogeography arising from seed flavohemoglobin; pleiotropy and emergent behavior

Description: Conduct a research program on weed biology to understand and characterize the most important weedy traits of the worst weeds in Iowa corn and soybean production systems, especially the seed behavior of the weedy foxtails.  Then, to elucidate the biotic and environmental factors regulating their behavior and to use this information to develop improved, sustainable weed management systems

Selected Publications:

• Dekker, J. 2004a. The evolutionary biology ofthe foxtail (Setaria) species-group.  In: Weed Biology and Management; Inderjit (Ed.). Kluwer Academic Publishers, The Netherlands. Pp. 65-113.

Vita: Click here to download

Website: Jack Dekker

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Jack Dekkers

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

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

• Functional and Structural Genomics-- Statistical methods for QTL detection and for estimating relationships between QTL and phenotype; identifying genes of economic importance in swine; 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 genetics, including design and optimization of breeding strategies, use of molecular genetic information, QTL detection, and economic aspects of breeding programs

Selected Publications:

• Chakraborty, R., L. Moreau, and J. C. M. Dekkers. 2001. A method to optimize selection on multiple identified quantitative trait loci. Genet. Sel. Evol. (Accepted).
• Malek, M., J.C.M. Dekkers, H.K. Lee, T.J. Baas, and M.F. Rothschild 2001. A molecular genome scan analysis to identify chromosomal regions influencing economic traits in the pig. II. Meat and muscle composition. Mammalian Genome 12:637-645.

Vita: Click here to download

Website: Jack Dekkers

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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:

• Yuting Yang*, Levent Engin, Eve Syrkin Wurtele, Carolina Cruz-Neira, Julie A. Dickerson, “Integration of metabolic networks and gene expression in virtual reality,” Bioinformatics, 2005.
• Ding, J., K. Viswanathan, D. Berleant, L. Hughes, E. S. Wurtele, D. Ashlock, J. A. Dickerson, A. Fulmer and P. S. Schnable (2005). "Using the biological taxonomy to access biological literature with PathBinderH." Bioinformatics 21(10): 2560-2562.
• Tang*, L. Shen, J.A. Dickerson, “BarleyExpress: a web-based submission tool for enriched microarray database annotations,” Bioinformatics, 21(3): 399-401, 200.

Vita: Click here to download

Website: Julie Dickerson

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Philip Dixon

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.

Vita: Click here to download

Website: Philip Dixon

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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: Our long-term research goals are to understand how proteins and nucleic acids achieve their functional three-dimensional structures and to elucidate rules that dictate interactions between proteins, nucleic acids and other molecules in cells.  In collaboration with several groups on campus, we have begun to integrate computational and experimental approaches to explore sequence-structure-function relationships in macromolecular complexes.  Current areas of focus include: prediction  and validation of ligand binding residues in proteins (for  protein, DNA, RNA and small molecules), rational design of zinc finger DNA binding proteins, prediction of functional effects of SNPs in unannotated proteins.

Selected Publications:

• An engineered zinc finger/target site design tool. Nucleic Acids Res., [Epub ahead of print]. In press.
• Terribilini, M., Sander, J., Lee, J.H., Zaback, P., Jernigan, R., Honavar, V., Dobbs, D. (2007) RNABindR:  A server for analyzing and predicting RNA binding sites in proteins. Nucleic Acids Res., [Epub ahead of print]. In press.
• Andorf, C., Dobbs, D. and Honavar, V. (2007) Exploring inconsistencies in genome-wide protein function annotations. BMC Bioinformatics. In press.
• EL-Manzalawy, Y., Dobbs, D., Honavar, V. (2007) PepMIL: A novel method for predicting flexible length MHC-II binding peptides. BMC Bioinformatics. In press
• Yan, C., Wu, F., Jernigan, R., Dobbs, D. and Honavar, V. (2007) Characterization of protein-protein interfaces. Protein J. In press.

Vita: Click here to download

Website: Drena Dobbs

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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:

Selected Publications:

• G. Dancik, K.S. Dorman, D.E. Jones (2006), 'An agent-based model for Leishmania infection'
• H. Zhou, K. S. Dorman. (2005), A branching process model of drug resistant HIV. In Deterministic and Stochastic Models for AIDS Epidemics and HIV Infections with Interventions, Hulin Wu and Wai-Yuan Tan, (eds)
• F. Fang, M.A. Suchard, V.N. Minin, K.S. Dorman (2005), 'A Bayesian phylogenetic model for testing recombination event'
• K. S. Dorman, X. Gu (2005), 'Bayesian inference for functional divergence'
• V. N. Minin, K. S. Dorman, M. A. Suchard (2004), 'Bayesian recombination identification: new models for incorporating prior information', Proceedings of the Joint Statistical Meetings, Section on Bayesian Statistical Science

Vita: Click here to download

Website: Karin Dorman

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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

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David Fernandez-Baca

Education: Ph.D., University of California, Davis, 1986

Research Interests: Combinatorial algorithms, with emphasis on sensitivity analysis of optimization problems and evolutionary tree construction

Description:

Selected Publications:

• D. Chen, O. Eulenstein, D. Fernández-Baca, and M.J. Sanderson. Minimum flip supertrees: Complexity and algorithms. To appear in IEEE Trans. Bioinformatics and Computational Biology.
• D. Fernández-Baca and B. Venkatachalam. Parametric sequence alignment. To appear in Handbook of Computational Molecular Biology (S. Aluru, ed.), Chapman and Hall/CRC Press Computer and Information Science Series, 2005, in press.
• F. Sun, D. Fernández-Baca, and W. Yu. Inverse parametric sequence alignment. Journal of Algorithms, 53(1):36--54 (2004).
• D. Chen, O. Eulenstein, and D. Fernández-Baca. Rainbow: A toolbox for phylogenetic supertree construction and analysis. Bioinformatics.

Vita: Click here to download

Website: David Fernández-Baca

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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:

Vita: Click here to download

Website: Rohan Fernando

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Shashi Gadia

Education: Ph.D., Illinois, Urbana-Champaign, 1977

Research Interests: Relational, object-oriented, and XML modeling for storage, query, and analysis

• Bioinformatics-- Relational, object-oriented, and XML modeling for storage, query, analysis, and exchange of genetic, temporal, spatial, and scientific-beliefs data
• Functional and Structural Genomics-- Same as above
• Genome Evolution-- Same as above

Description: Temporal, spatial, belief, security, stastical and incomplete data; database models, type hierarchy, languages, user interfaces, optimization, implementation and access methods; pattern matching in spatio-temporal data

Selected Publications:

Vita: Click here to download

Website: Shashi Gadia

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M. H. West Greenlee

Education: Ph.D., Iowa State, 1999

Research Interests: The molecular basis of neural differentiation

Description:

Selected Publications:

Vita: Click here to download

Website: M. Heather West Greenlee

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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:

• Gao X, Vander Velden KA, Voytas DF and Gu X* (2005) SplitTester: software to identify domains responsible for functional divergence in protein family BMCBioinformatics 2005, 6:137
• Gu, X*, Huang, W., Xu, D., Zhang, H.(2005) GeneContent: software for whole-genome phylogenetic analysis. Bioinformatics 21(8):1713-1714 .
• Sen, T*, Kloczkowski, A., Jernigan, R., Yan, C., Honavar, V., Ho, K., Wang, C., Ihm, Y. Cao, H., Dobbs, D.,Gu, X. (2004) Prediction of binding sites of hydrolase-inhibitor complexes by combining several methods. BMC Bioinformatics. 5:205.

Vita: Click here to download

Website: Xun Gu

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Mark Hargrove

Education: Ph.D., Rice, 1995

Research Interests: Structural biology, heme protein structure-function, X-ray crystallography

• Macromolecular Structure and Function-- Heme protein structure and function; X-ray crystallography

Description: The structure, function, folding, and expression of heme proteins. Heme proteins exhibit marked differences in reactivity toward diatomic ligands such as O2, CO, and NO, all of which are important biological molecules. However, unlike most enzymatic reactions which rely on the exact shape and charge distribution of the substrate molecule to determine specificity, selective recognition of small diatomic ligands by heme proteins occurs after the heme-ligand complex is formed

Selected Publications:

• Hargrove, M.S.(2005) Ligand binding with stopped-flow rapid mixing. Methods Mol. Biol. 305,323-342.

Vita: Click here to download

Website: Mark Hargrove

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Kai-Ming Ho

Education: Ph.D., Berkeley, 1978

Research Interests: Protein structure prediction

• Macromolecular Structure and Function-- Protein structure prediction

Description:

Selected Publications:

Vita: Click here to download

Website: Kai-Ming Ho

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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?
Additional information about current projects can be found at www.cild.iastate.edu   

Selected Publications:

• Andorf, C., Silvescu, A., Dobbs, D., and Honavar, V. (2007) Detecting Inconsistencies in Gene Ontology Protein Function Annotations: A MachineLearning Approach. BMC Bioinformatics. In press.
• Bao, J., Slutzki, G., and Honavar, V. (2007). A Semantic Importing Approach to Reusing Knowledge from Multiple Autonomous Ontology Modules. In: Proceedings of the 22nd Conference on Artificial Intelligence (AAAI-2007).
• Bao, J., Slutzki, G. and Honavar, V. Privacy-Preserving Reasoning on the Semantic Web. ACM/WIC/IEEE International Conference on Web Intelligence, San Jose, CA, In press, 2007.
• Bao, J., Slutzki, G., and Honavar, V. Distributed Reasoning with Modular ALC Ontologies (ALCP). Web Intelligence and Agent Systems. Vol. In press, 2007.
• Caragea, C., Sinapov, J., Terribilini, M., Dobbs, D. and Honavar, V. Assessing the Performance of Macromolecular Sequence Classifiers. IEEE Conference on Bioinformatics and Bioengineering, In press.
• Dunn-Thomas, T., Dobbs, D.L., Sakaguchi, D. Young, M.J. Honavar, V. Greenlee, H. M. W. (2007). Proteomic Differentiation Between Murine Retinal and Brain Derived Progenitor Cells. Stem Cells and Development.  In press.
• El-Manzalawy, Y., Dobbs, D. and Honavar, V.  (2007) PepMIL: A Novel Method for Predicting Flexible Lengths MHC-II binding Peptides. In press. 2007.
• Hecker, L., Alcon, T., Honavar, V., Greenlee, H. (2007). Querying multiple large-scale gene expression datasets from the developing retina using a seed network to prioritize experimental targets. To appear.
• Pathak, J., Basu, S., and Honavar, V. (2007). On Context-Specific Substitutability of Web Services. Proceedings of the IEEE International Conference on Web Services, IEEE. 2007.
• Terribilini, M., Sander, J.D., Lee, J-H., Zaback, P., Jernigan, R.L., Honavar, V. and Dobbs, D. (2007). RNABindR: A Server for Analyzing and Predicting RNA Binding Sites in Proteins. Nucleic Acids Research. Vol. 35. No. 9. pp. doi:10.1093/nar/gkm2, 2007
• Wu, F., Towfic, F., Dobbs, D. and Honavar, V. (2007) Analysis of Protein Protein Dimeric Interfaces. IEEE International Conference on Bioinformatics and Biomedicine, San Jose, In press, 2007.
• Yan, C., Wu, F., Jernigan, R.L., Dobbs, D., Honavar, V. (2007) Analysis of Protein-Protein Interfaces. Proteins. In press.
• Bao, J., Caragea, D., and Honavar, V. (2006). A Tableau-based Federated Reasoning Algorithm for Modular Ontologies. ACM / IEEE / WIC Conference on Web Intelligence, Hong Kong, pp. 404-410.
• Bao, J., Hu, Z., Caragea, D., Reecy, J., and Honavar, V. (2006). 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.
• Bao, J., Caragea, D., and Honavar, V. (2006). Modular Ontologies - A Formal Investigation of Semantics and Expressivity. In Proceedings of the First Asian Semantic Web Conference, Beijing, China, Springer-Verlag  Lecture Notes in Computer Science, Vol. 4185, pp. 616-631. Best paper award.
• Caragea, D., Zhang, J., Pathak, J., and Honavar, V. (2006). Learning Classifiers from Distributed, Ontology-Extended Data Sources. Proceedings of the 8th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2006), Krakov, Poland, Lecture Notes in Computer Science. Berlin: Springer. Vol. 4081. pp. 363-373
• Pathak, J., Basu, S., Lutz, R., and Honavar, V. (2006).  Selecting and Composing Web Services Through Iterative Reformulation of Functional Specifications.  Proceedings of the IEEE International Conference on Tools With Artificial Intelligence (ICTAI 2006), Washington, DC, IEEE. Best Paper Award.
• Terribilini, M., Lee, J-H., Yan, C., Honavar, V. and Dobbs, D. (2006). Identifying Interactions in Recalcitrant Proteins. Predicted Protein and RNA binding sites in REV proteins of HIV and EIAV agree with experimental data. In: Proceedings of the Pacific Symposium on Biocomputing, Hawaii, World Scientific. Vol. 11. pp. 415-426.
• Terribilini, M., Lee, J.H., Yan, C., Jernigan, R., Honavar, V., and Dobbs, D. (2006). Computational Prediction of Protein-RNA Interfaces. RNA Journal.. Vol. 12. No. 1450. pp. 1462, 2006.
• Yan, C., Terribilini, M.,  Wu, F., Jernigan, R.L., Dobbs, D. and Honavar, V. (2006). Identifying amino acid residues involved in protein-DNA interactions from sequence. BMC Bioinformatics. Vol. 7. pp. 262-, 2006.
• Zhang, J., Silvescu, A., Kang, D-K., and Honavar, V. (2006). Learning Compact and Accurate Naive Bayes Classifiers from Attribute Value Taxonomies and Partially Specified Data. Knowledge and Information Systems. Vol. 9. No. 2. pp. 157-179, 2006.
• Caragea, D., Zhang, J., Bao, J., Pathak, J., and Honavar, V. (2005). Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed, Information Sources. Invited paper. In: Proceedings of the Conference on Algorithmic Learning Theory. Lecture Notes in Computer Science. Vol. 3734. Berlin: Springer-Verlag. pp. 13-44.
• Lonosky, P.,  Zhang, X., Honavar, V., Dobbs, D., Fu, A., and Rodermel, S. (2004) A Proteomic Analysis of Chloroplast Biogenesis in Maize.  Journal of Plant Physiology. Vol. 134, pp. 560-574, 2004. Yan, C., Dobbs, D., and Honavar, V. (2004).
• A Two-Stage Classifier for Identification of Protein-Protein Interface Residues. Bioinformatics. 20. pp. i371-378, 2004. (Also presented at the Conference on Intelligent Systems in Computational Biology, 2004)
• Silvescu, A. and Honavar, V. (2001). Temporal Boolean Network Models of Genetic Networks and Their Inference from Gene Expression Time Series. Complex Systems. Vol. 13. No. 1. pp. 56-78.

Vita: Click here to download

Website: Vasant Honavar

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Mei Hong

Education: Ph.D., Berkeley, 1996

Research Interests: Solid-state NMR studies of the structure and dynamics of membrane proteins and fibrous biopolymers

• Macromolecular Structure and Function-- Determination of the structure and dynamics of membrane-bound proteins and fibrous biopolymers by solid-state NMR

Description: To elucidate the structure and dynamics of membrane proteins, fibrous protein aggregates, and other insoluble macromolecules important in biology

Selected Publications:

• M. Tang, A.J. Waring, and M. Hong, "Intermolecular Packing and Alignment of a β-Hairpin Peptide from 2D Solid-State NMR", J. Am. Chem. Soc. , 2005, in press.
• W. Luo, X.L. Yao and M. Hong, "Evidence of Large Structure Rearrangement of Colicin Ia Channel Domain Due to Membrane Binding from 2D 13C Spin Diffusion NMR", J. Am. Chem. Soc., 2005, 127, 6402-8.

Vita: Click here to download

Website: Mei Hong

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Richard Honzatko

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

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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.

Vita: Click here to download

Website: Xiaoqiu Huang

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Fred Janzen

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:

• Krenz, J. G., G. J. P. Naylor, H. B. Shaffer, and F. J. Janzen. 2005. Molecular phylogenetics and evolution of turtles. Molecular Phylogenetics and Evolution 37:178-191.
• Kuo, C.-H., and F. J. Janzen. 2004. Genetic effects of a persistent bottleneck on a natural population of ornate box turtles (Terrapene ornata). Conservation Genetics 5:425-437.
• Kuo, C.-H., and F. J. Janzen. 2003. BottleSim: a bottleneck simulation program for long-lived species with overlapping generations. Molecular Ecology Notes 3:669-673. (Software available at http://www.arches.uga.edu/~chkuo/setsoft.html)
• Kolbe, J. J., and F. J. Janzen. 2002. Spatial and temporal dynamics of turtle nest predation: edge effects. Oikos 99:538-544.
• Janzen, F. J., and H. S. Stern. 1998. Logistic regression for empirical studies of multivariate selection. Evolution 52:1564-1571. (Software available at http://www.public.iastate.edu/~fjanzen/software/regress.htm)

Vita: Click here to download

Website: Fred Janzen

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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.

• Selected Publications:
• Sen TZ and Jernigan RL Optimizing cutoff distances and spring constants for the Gaussian Network Model of ATP-binding proteins, in “Normal Mode Analysis: Theory and Applications to Biological and Chemical Systems,” 2006, Eds. I. Bahar and Q. Cui, Chapman and Hall/CRC, Boca Raton, pp 171-186.
• Kurkcuoglu O, Jernigan RL and Doruker P Loop Motions of Triosephosphate Isomerase Observed with Elastic Networks, Biochemistry, 2006;45:1173-1182.
• Song G and Jernigan RL An enhanced elastic network model to represent the motions of domain-swapped proteins. Proteins, 2006;63:197-209.
• Terribilini M, Lee, JH, Yan C, Jernigan RL, Honavar V and Dobbs D (2006) Prediction of Protein-RNA Interfaces. RNA, 2006; 12: 1450-1462.
• Sen TZ, Feng Y, Garcia JV, Kloczkowski A and Jernigan RL The extent of cooperativity of protein motions observed with elastic network models is similar for atomic and coarser-grained models. J. Chem. Thy. Comput., 2006; 2, 696-704.
• Sen TZ, Kloczkowski A and Jernigan RL A DNA-Centric Look at Protein-DNA Complexes. Structure, 2006; 14:1341-2.
• Jernigan RL and Kloczkowski Packing regularities in biological structures relate to their dynamics. Methods Mol Biol, 2006; 350:251-76.
• Sen TZ, Kloczkowski A and Jernigan RL Functional clustering of yeast proteins from the protein-protein interaction network. BMC Bioinformatics. 2006; 7:355.
• Yan C, Terribilini M, Wu F, Jernigan RL, Dobbs D and Honavar V Predicting DNA-binding sites of proteins from amino acid sequence. BMC Bioinformatics, 2006;7:262.
• Sen TZ, Cheng H, Kloczkowski A and Jernigan RL A Consensus Data Mining secondary structure prediction by combining GOR V and Fragment Database Mining. Protein Sci, 2006; 15:2499-2506.
• Terribilini M, Lee JH, Yan C, Jernigan RL, Carpenter S, Honavar V, and Dobbs D Identifying interaction sites in "recalcitrant" proteins: predicted protein and RNA binding sites in rev proteins of HIV-1 and EIAV agree with experimental data. Pac. Symp. Biocomp. 2006;415-26.
• Pokarowski P, Kloczkowski A, Nowakowski S, Pokarowska M, Jernigan RL and Kolinski A Ideal Amino Acid Exchange Forms for Approximating Substitution Matrices. Proteins, in press. Peto M, Kloczkowski A and Jernigan, RL. Shape-dependent designability studies of lattice proteins. J. Phys.: Cond. Matter, in press.

Vita: Click here to download

Website: Robert Jernigan

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Douglas Jones

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

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Suresh Kothari

Education: Ph.D., Purdue, 1977

Research Interests: Parallel and distributed computing and its applications in science and engineering. Specific topics of interest are: tools for parallelization of legacy codes, parallel performance models, and distributed processing systems

• Bioinformatics--Parallel and distributed computing; neural networks

Description:

Selected Publications:

Vita: Click here to download

Website: Suresh Kothari

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Susan Lamont

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.
Vita: Click here to download

Website: Susan Lamont

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Dennis Lavrov

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

Research Interests: Comparative analysis of mitochondrial genomes from diverse animal groups and the use of gene order data for the analysis of ancient metazoan relationships

• 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. 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

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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.
• C.J. Lawrence, M.L. Schaeffer, T.E. Seigfried, D.A. Campbell, and L.C. Harper, MaizeGDB's new data types, resources, and activities, Nucleic Acids Research 35(Database issue): D895-900, 2007.
• Predicting chromosomal locations of genetically mapped loci in maize using the Morgan2McClintock Translator, C.J. Lawrence, T.E. Seigfried, H.W. Bass, and L.K. Anderson, Genetics, 172(3):2007-2009, 2006
• The Maize Genetics and Genomics Database. The community resource for access to diverse maize data, Author(s): C.J. Lawrence, T.E. Seigfried, and V. Brendel, Plant Physiol, 138:55-58, 2005
• Comparative plant genomics resources at PlantGDB, Q.F. Dong, C.J. Lawrence, S.D. Schlueter, M.D. Wilkerson, S. Kurtz, and V. Brendel, Plant Physiol, 139:610-618, 2005
• A standardized kinesin nomenclature, C.J. Lawrence, R.K. Dawe, K.R. Christie, D.W. Cleveland, S.C. Dawson, S.A. Endow, L.S.B. Goldstein, H.V. Goodson, N. Hirokawa, J. Howard, R.L. Malmberg, J.R. McIntosh, H. Miki, T.J. Mitchison, Y. Okada, A.S.N. Reddy, W.M. Saxton, M. Schliwa, J.M. Scholey, R.D. Vale, C.E. Walczak, and L. Wordeman, Journal of Cell Biology, 167(1):19-22, 2004
• LumberJack: a heuristic tool for sequence alignment exploration and phylogenetic inference, C.J. Lawrence, C.M. Zmasek, R.K. Dawe, and R.L. Malmberg, Bioinformatics, 20(12):1977-1979, 2004
• MaizeGDB: the community database for maize genetics and genomics, C.J. Lawrence, Q. Dong, M.L. Polacco, T.E. Seigfried, and V. Brendel, Nucleic Acids Research, 32:D42-53, 2004
• PGROP – a gateway to plant genome research outreach programs, S.B. Baran, C.J. Lawrence, and V. Brendel, Plant Physiol, 134(3):889, 2004
Vita: Click here to download

Website: Carolyn Lawrence

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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

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Charles Link Jr.

Education: M.D., Stanford, 1985

Research Interests: Evaluation of cancer causes using high through-put genomic applications

• Functional and Structural Genomics-- Dr. Link's laboratory is interested in developing and applying high through-put genomic applications to evaluate the root causes of human cancer. This requires approaches to interface biological data with computers and to process and sort information in a useful way to advance the understanding of gene function in cancer cells

Description:

Selected Publications:

Vita: Click here to download

Website: Charles Link, Jr.

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Peng Liu

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

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Gustavo MacIntosh

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

Research Interests: Gene expression and metabolic changes during plant defense responses to pests; functional genomics of plant nucleases.

• Macromolecular Structure and Function-- Gene expression and metabolic changes during plant defense responses to pests; functional genomics of plant nucleases.

Description:

Selected Publications:

Vita: Click here to download

Website: Gustavo MacIntosh

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Roger Maddux

Education: Ph.D., Berkeley, 1978

Research Interests: Relation algebras, logic, combinatorics, mathematical ecology

• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking-- Genetic/adaptive/evolutionary/combinatorial algorithms; temporal/spatial computational models of plant populations; ecological restoration, species-area relation, poaceae

Description:

Selected Publications:

Vita: Click here to download

Website: Roger Maddux

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Surya Mallapragada

Education: Ph.D., Purdue University, 1996

Research Interests: Designing polymers with tailored micro/nanostructures

• Macromolecular Structure and Function-- Our research program is focused on designing polymers with tailored micro/nanostructures, both at the surface as well as in the bulk, with relevance to technological and bioengineering applications. Fundamental investigations of molecular attributes, as well as studies of macroscopic performance are linked together to investigate the relationship between the two

Description:

Selected Publications:

Vita: Click here to download

Website: Surya Mallapragada

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John Mayfield

Education: Ph.D., Pittsburgh, 1968

Research Interests: The goal of my research is to develop a generalized theory of evolution that relates naturally to fundamental mathematical and physical concepts of complexity.

• Genome Evolution-- Evolutionary theory; molecular genetics

Selected Publications:

• John E. Mayfield (2007) Minimal History, a Theory of Plausible Explanation. Complexity (in press)
• John E. Mayfield. (2006) Evolution as Computation. Evolutionary Theory (in press)

Vita: Click here to download

Website: John Mayfield

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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

Description:

Selected Publications:

Vita: Click here to download

Website: Leslie Miller

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Allen Miller

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.  Because of similarities in replication mechanisms across kingdoms, this knowledge may be relevant to major human viruses such as hepatitis A and C viruses, dengue, West Nile, and even SARS.  At a more fundamental level, 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 and how the genetic code in nucleic acids is converted to amino acid sequence in functional proteins.  This knowledge may allow us to modify viral sequences and mechanisms to control expression of host and trans-genes in beneficial ways.

Sustainable control of crop diseases and pests

We strive to improve the knowledge base of plant pathologists and breeders, in poor and developed countries, who work to control barley yellow dwarf and cereal yellow dwarf viruses and the aphids that transmit them.  BYDV and CYDV are the most economically important viruses of wheat, barley and oats, worldwide.  Many isolates exist.  They are poorly characterized and vary remarkably in sequence.  In a multinational collaborative project, we are determining and maintaining a database of the complete nucleotide sequences of dozens of BYDV and CYDV isolates from around the world.  We are also interested in exploiting aphid-transmitted viruses to control aphids.

Selected Publications:

• Shen R, Miller WA (2007) Structures required for poly(A) tail- independent translation overlap with, but are distinct from, cap- independent translation and RNA replication signals at the 3' end of Tobacco necrosis virus RNA. Virology 358, 448-458.
• Boyapalle S, Pal N, Miller WA, Bonning BC (2007) A glassy-winged sharpshooter cell line supports replication of Rhopalosiphum padi virus (Dicistroviridae). Journal of Invertebrate Pathology 94, 130­139.
• Banerjee AK, Chatterjee M, Yu YY, Suh S-G, Miller WA, Hannapel DJ (2006) Dynamics of a mobile RNA of potato involved in a long-distance signaling pathway. Plant Cell 18, 3443-3457. Miller WA, White KA (2006) Control of plant virus gene expression and replication by long-distance RNA-RNA interactions. Annual Review of Phytopathology 44, 447-467.
• Shen R, Rakotondrafara AM, Miller WA (2006) trans regulation of cap- independent translation by a viral subgenomic RNA. Journal of Virology 80, 10045-10054.
• Rakotondrafara AM, Polacek C, Harris E, Miller WA (2006) Oscillating kissing stem-loop interactions mediate 5' scanning-dependent translation by a viral 3' cap-independent translation element. RNA 12, 1893-1906.
• Dreher TW, Miller WA (2006) Translational control of positive strand RNA plant viruses. Virology 344, 185-197. Pettit Kneller EM, Rakotondrafara AM, Miller WA (2006) Cap- independent translation of plant viral RNAs. Virus Research 119, 63-75.
• Shen, Ruizhong, and W.A. Miller. 2004. The 3' Untranslated Region of Tobacco Necrosis Virus RNA Contains a Barley Yellow Dwarf Virus-Like Cap-Independent Translation Element. Journal of Virology. 78(9), 4655-4664.

Vita: Click here to download

Website: W. Allen Miller

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Chris Minion

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.

Vita: Click here to download

Website: Chris Minion

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Kirk Moloney

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

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Alan Myers

Education: Ph.D., Duke, 1983

Research Interests: mRNA and polypeptide profiling, predictions and modeling of protein structures

• Functional and Structural Genomics-- Gene identification in nucleotide sequence databases, mRNA and polypeptide profiling, predictions and modeling of protein structures, and global analysis of metabolism
• Macromolecular Structure and Function-- Same as above

Description:

Selected Publications:

• Zhang, X., Myers, A.M. and James, M.G. (2005) Mutations affecting starch synthase III in Arabidopsis alter leaf starch structure and increase the rate of starch synthesis. Plant Physiol. 138,663-674.
• Morell, M.K. and Myers, A.M. (2005) Towards the rational design of cereal starches. Curr. Opin. Plant Biol. 8, 204-210.
• Zhang, X., Colleoni, C., Ratushna, V., Sirghie-Colleoni, M., James, M.G. and Myers, A.M. (2004) Molecular characterization demonstrates that the Zea mays gene sugary2 codes for starch synthase isoform SSIIa. Plant Mol. Biol. 54, 865-879.

Vita: Click here to download

Website: Alan Myers

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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

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Basil Nikolau

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

Research Interests: Biochemistry and molecular biology of biotin and biotin-containing enzymes; Regulation of plant lipid metabolism

• 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