The Andreotti laboratory is interested in issues of protein structure and molecular recognition. Nuclear magnetic resonance (NMR) spectroscopy is a primary research tool in the lab and is used to solve protein structures, analyze protein mediated interactions and measure dynamic motions of proteins. All of the information gleaned from structural studies is used to formulate a better understanding of protein function in vivo.
Evolution of the Rps1 region: We are interested in the evolution of Phytophthora disease resistance genes in soybean. Recently we have cloned the Rps1 locus that carries five functional Phytophthora resistance genes. We have identified the Rps1-k gene from this locus. Nearly 220 kb DNA from the Rps1 region has been sequenced. We are looking for a graduate student with bioinformatics and computational experiences, who will study the evolution of this region across legume species.
Functional genomics of plant susceptibility and resistance to bacterial diseases.
Comparative genomics of plant pathogenic bacteria.
Bacterial type III effector gene mining using a combination of sequence analysis and reporter screen approaches
.
Bioinformatic approaches to gene discovery in bacterial regulation of pathogenicity .
Microarray analyses of rice responses to bacterial pathogens, using three-dye labeling.
Microarray hybridizations for identifying deletion mutations in rice.
Identification and analysis of soybean homologues of Pto, a disease resistance gene from tomato, and functional characterization of candidates using transient expression and protein-protein interaction assays.
Visual Tools for Assisting the Analysis of Gene Expression Data and Metabolic Networks
The research involves developing methodology and software for visualizing high-dimensional data and networks. We have software built upon the open source packages R (www.R-project.org) and GGobi (www.ggobi.org) that make it easier for biologists to use the statistical analysis methods of R and the high interaction graphics of GGobi for data analysis. Our project web page is currently
www.public.iastate.edu/~kyung/GeneGobi.html. Work with 1 post-doc, 1 MS student and 2 undergraduate students on a project.
In addition to wet lab studies to understand RNA-protein interactions during the course of E. coli 30S ribosomal subunit assembly, we are currently engaged in a collaboration with members of the Virtual Reality Applications Center (VRAC) to study the structure and movement of the ribosome. These studies involve developing methods for viewing 3-D structures in the C6 virtual reality cave and then incorporating movement within these molecules. We hope that these applications will be of use to any investigator interested in dynamics and complicated structures.
Spring Only I am looking for someone to help piece together metabolic pathways in Arabidopsis and someone to help apply graph theoretic methods to existing networks using the LEDA package (requires a strong math background.)
The Dobbs group focuses on analysis and prediction of macromolecular structure-function relationships. We are involved in several collaborative research projects in which we welcome the participation of BCB rotation students!
Protein structure prediction: prediction of protein 3-dimensional structure from amino acid sequence; identification of structural similarities in proteins with little sequence similarity; development of rapid structural threading algorithms for genome-wide screening. Current projects include:
Comparative analysis, computational prediction and experimental determination of 3-dimensional structure of HIV rev and related proteins (with Kai-Ming Ho, Physics & Susan Carpenter, VMRI) The HIV rev protein is critical for viral replication and offers a potential target for clinical intervention in AIDS, but has so far eluded experimental structure determination. Our predicted structures for HIV rev and the equine (EIAV) rev proteins suggest a potential explanation for difficulties encountered in structure determination efforts and offer a possible mechanism for circumventing these problems. Rotation students may participate in experimental (wet lab) tests of predicted rev structures and/or in comparative analysis of functional effects of mutations on rev function in vivo (computational and wet lab).
Computational prediction and experimental identification of potential ligands for the crinkly 4 receptor kinase in Arabidopsis (with Kai-MIng Ho, Physics & Phil Becraft, GDCB)
The crinkly 4protein plays critical roles in cellular development and differentiation in maize and Arabidopsis. It contains an extracellular domain that resembles mammalian Tumor Necrosis Factor (TNF) receptors, but the cognate ligand for crinkly 4has not yet been identified. We have developed a rapid structural threading algorithm for screening the entire Arabidopsis genome for potential crinkly 4 ligands and are testing predicted candidates for their function in vivo.
Analysis and prediction of protein sequence-structure-function relationships: identification of regulatory conformational changes mediated by proline cis-trans isomerization; discovery of sequence correlates of protein structure and function; prediction of binding sites in proteins from amino acid sequence information. Current projects include:
Computational identification and biophysical analysis of regulatory structural transitions directed by prolinecis-trans isomerization. (with Amy Andreotti, BBMB)
In NMR studies of the regulation of Tec family tyrosine kinases, the Andreotti group discovered a novel molecular switch: a dramatic conformational change mediated by cis-trans isomerization of proline residues. A "proline switch" in the Itk tyrosine kinase determines the specificity of Itk protein-protein interactions by regulating the ransition between two alternative binding surfaces. Current work is directed at identifying the molecular determinants of proline isomerization and exploring whether native-state proline isomerization may be a wide-spread regulatory mechanism. Rotation students may participate in experimental (NMR) structural analysis of proline isomerization and/or computational identification and analysis of sequence/structural determinants of cis-trans proline isomerization.
Computational prediction of protein-protein interactions using data-driven approaches (with Vasant Honavar, Com Sci & Bob Jernigan, BBMB)
We are developing knowledge-based approaches for predicting functionally important residues in proteins. Our current focus is prediction of amino acid residues that participate in protein-protein interactions from amino acid sequence information, using a variety of data-driven approaches and algorithms (Naive Bayes, Support Vector Machines, etc.). Rotation students may participate in development and evaluation of algorithms and software, and/or development of a web-based protein-interaction prediction server.
(7/22/04)
Karin DORMANStatistics and Genetics, Cellular & Developmental Biology
The Dorman lab has opportunities in statistical phylogenetics and stochastic modeling applied to evolution, genetics, and epidemiology, especially as it relates to medically or economically important viruses. Current research projects and opportunities are available on the lab web page at www.biomath.org/dormanks
We offer algorithmic projects to solve problems in molecular biology. To participate you need an algorithmic background (e.g. Com S 311 or equivalent).
The goal of this project is to research XML based infrastructural technology for the development of models, storage, exploration, query, and
analysis of data in biology. We are also interested in developing XML based database applications in bioinformatics.
Laboratory for Database Models and Access
This lab undertakes the research, development, implementation, and prototyping of models and languages for storage, query, and exploration of
data that arises in specialized problem domains where existing database technologies do not provide adequate solutions.
Currently, we work on two major aspects of data modeling that are not necessarily mutually exclusive: parametric data and semistructured data.
Under the parametric banner, we study the role of time, space (geography), and belief dimensions in databases. On the semistructured data front, we
build state of the art technology within and beyond the industry standard framework of XML (Extensible Markup Language).
We are currently applying our know-how to database paradigms for bioinformatics, meteorology, and software engineering. Meteorology is an example
where all three types of dimensions under the parametric banner are present. On the other hand, software engineering and bioinformatics are
benefiting under XML. We continue to seek other application domains needing specialized approaches for their database needs.
Current research in Honavar's lab in
Bioinformatics and Computational Molecular Biology is focused on development of computational tools for largescale collaborative
data-driven knowledge discovery in biological sciences and the application of the resulting tools in data-driven exploration of macromolecular
sequence-structure-expression-evolution-function relationships and inference of complex biological signalling networks and pathways. Much of
this work is being carried out in collaboration with colleagues who have expertise in molecular biology (Drena Dobbs), biochemistry, genetics,
neuroscience (Heather West-Greenlee), and biophysics (Robert Jernigan). This work is supported in part by an Information Technology Research (ITR)
grant (0219699) from the National Science Foundation and a Biological Information Science and Technology Initiative (BISTI) award (GM0663!
87) from the National Institutes of Health and graduate fellowships from Pioneer Hi-Bred and IBM. Rotation projects can be arranged in any of the
areas of current research focus including:
Development of computational tools for interactive and collaborative data-driven knowledge discovery from disparate biological information sources including macromolecular sequences, structures, phylogenies, expression patterns. Of particular interest are algorithms and software for
rapid and flexible ontology-guided information extraction from heterogeneous, distributed, autonomous information sources
learning classifiers, associations, and clusters from distributed autonomous information sources
learning compact and comprehensible classifiers from attribute value taxonomies, class taxonomies, and partially specified data
learning attribute value taxonomies and class taxonomies from data
learning classifiers from multi-relational data
Data-driven exploration of macromolecular sequence-structure-expression-evolution-function relationships including
Discovery of sequence correlates of protein function and protein-protein interaction
Discovery of sequence correlates of functionally significant structural features of proteins
Construction of classifiers for assigning protein sequences to structural for functional families
Prediction of putative binding sites in proteins from sequence information
Data-driven inference of genetic networks, metabolic networks, and signaling pathways including
Discovery of coexpressed or coregulated genes from gene expression patterns
Construction of genetic networks from gene expression data
Analysis of gene expression patterns in specific systems (e.g., onset of photosynthesis, retinal development)
Modeling and simulation of complex genetic networks, metabolic networks, and signaling pathways
Students wishing to join Honavar's lab should be familiar with fundamentals of computer science, statistics, and be comfortable with programming (see http://www.cs.iastate.edu/~honavar/notebioinformatics.html). However, rotation students with a strong background in biological sciences who are interested in establishing collaborations with Honavar's lab without necessarily joining the laboratory are welcome.
(7/16/03)
Fred JANZENEcology, Evolution & Organismal Biology
Wet lab work--Major projects in my lab concern (a) microsatellite DNA analyses of paternity and population genetic structure and (b) DNA sequencing analyses to determine phylogeographic relationships among populations and phylogenetic relationships among species.
Molecular evolution/ecology--A number of projects could be undertaken, including examining the molecular structures of sodium channels of the only organism known to be resistant to the otherwise deadly neurotoxin called tetrodotoxin.
Computational biology--Computational projects in my lab include (a) developing algorithms and statistical models of natural selection (which can be "proofed" with real data sets), (b) creating a relational database for handling population, genotypic, genealogical, etc. information on individuals, populations, and species for subsequent mining, and (c) using geographic information systems (i.e., GIS) to analyze higher-order relationships among ecological, environmental, genetic, and behavioral data that are spatially- and temporally-structured.
Please contact me for more detailed information. fjanzen@iastate.edu
(7/31/03)
The chicken is the first food animal species to have its genome completely sequenced. Our lab has a strong history of structural and functional genomics in the immune response of chickens. Recently, we have participated in the International Chicken SNP project, which has identified 2.8 million SNPs in the chicken genome. Rotation projects could be either wet lab work to determine associations of genetic variation with important biological traits, or bioinformatics studies to mine genes or to enhance tools for use of the chicken genome sequence. (8/18/04)
predicting mRNA structure that controls its interaction with the ribosome during protein synthesis. It will involve primarily viral sequences, but also eukaryotic mRNAs in general are an important subject.
RNA-protein interactions is also part of the project, so some protein modeling is possible.
The control of virus replication by its RNA structure and the switch between translation and replication will also be studied. See: Guo et al. (2001) Mol. Cell 7, 1103-1109; and Barry & Miller (2002) PNAS 99, 11133-11138. Although this is primarily a plant virus lab, modeling of human mRNAs and RNAs of human viruses will be encouraged.
This is a wet lab with expertise in the molecular biology side of research, not computer science or bioinformatics.
I would like a BCB student to participate in a world-wide plant virus sequencing project.
Project involves sequence assembly, alignment, annotation, database management, RNA structure analysis, and more.
Mechanisms of protein synthesis and RNA replication are also possible.
Xiaowu Gai of the Baker Center is a co-PI on the project.
Please note that I may also be entertaining rotating students from MCDB, BBMB, IG, and I can most likely accept only one student, so there are no guarantees. But I would really like some computer expertise added to my lab.
(7/22/03)
Chris Minion (my web site is:
http://mycoplasmas.vm.iastate.edu/lab_site/index.html ) Veterinary Microbiology
and Preventive Medicine
My laboratory is presently engaged in the construction of microarrays for several bacterial pathogens. These include Mycoplasma hyopneumoniae,
E. coli O157:H7 and Listeria monocytogenes. We are also working on a microarray for the pig lung to study host-pathogens interactions. If a student
is interested in microbial pathogenesis, this is a golden opportunity to get some valuable wet lab experience and learn some new exciting techniques.
Data mining will be an important part of the overall experience.
Compile and categorize a list of sources with all publicly available nucleotide and protein sequences.
Annotate each source entry with useful info (The nature; Volume; Availability; Form of availability; Associated information; How updated; etc.)
Come up with a way or ways to automatically gather such info.
Requirements:
Knowledge of molecular biology and genome works
Skills using PC for internet information exploring
Some practical programming skills like perl
Develop a database structure to archive animal genome related bioinformatics/ genetics/ genomics software.
Design a relational db table structure
Implement the db structure in MySQL or Postgres
Parse and upload given data
Develop a web interface for searching the db
BONUS: Develop an administrative interface to manage the db (input/update/etc)
Requirements:
Knowledge of basic genetics and genome analysis
Knowledge of relational database, DBI/DBD
Some practical programming skills like perl
Develop a text mining tool in C++, perl, java or other languages (depending on the skills, experience and desire, this work can be on various levels - for example a low level can be a simple text based search tool; a high level can be an intelligent tool to make a thesis).
Requirements:
Knowledge of basic molecular biology and genome studies
We have more than 240,000 BAC end sequences averaging 450 bp each, that can be analyzed by a student to study the diversity and evolution of repetitive DNA sequences in soybean. Or........
The rotation student could work closely with senior personnel to determine the types and frequencies of alternative splicing in soybean through comparisons of soybean EST consensus sequences with soybean and Arabidopsis genomic sequences.
Embryogenomics- my lab is using both wet lab and bioinformatic approaches to identify and study genes controlling early mammalian embryo
developmental processes. We use two types of datasets, both developed in my wet lab, in collaborations with bioinformatics groups:
Gene Expression profiles developed by comparing mRNA expression from a novel transgenic mouse line with non-transgenic littermates. This
line has sensory and anatomical defects in the central nervous system (CNS) where over-expression of an important transcriptional regulator (Hoxa5) is
observed in the brachial spinal cord. The hypothesis is that Hoxa5 ectopic expression causes these defects. We want to discover the genetic
perturbations caused by Hoxa5, for which no spinal cord targets are known, at the molecular level. This project is part of a larger project, funded
by NIH, to understand the expression and function of Hoxa5 in the CNS and other tissues.
Gene Expression profiles developed by comparing mRNA expression from various stages of porcine embryonic development, and from the corresponding
uterine tissue, during the crucial stage of implantation. This is a project to develop an understanding of the role that maternal-fetal
communications play in proper embryo development. An important additional aspect of this research is understanding the role that immunology plays
in this process. A collaboration has been developed with both a reproductive biologist and an immunologist in this project, and we have recently
received USDA support for this project. (8/12/03)
We study the evolutionary ecology of phenotypic plasticity in vertebrates, and are looking at the genetic basis of alternative sex determining mechanisms, their ecological context, and their evolution from a developmental/molecular to a population dynamic perspective. See website (http://www.public.iastate.edu/~nvalenzu/)for more information on research areas. Rotation opportunities in my lab would include modeling the evolution of sex ratio and population dynamics under different environmental and natural selection regimes. People with computational and programming skills who are interested in these topics can contact me for further details.
Research interests: molecular evolution, genome evolution, and phylogenetics of higher plants. In my laboratory we use molecular and genetic tools to explore the manner in which DNA sequences and genomes change over evolutionary time, as well as the relationship between these events and morphological change. We have a particular interest in the mysterious and common phenomenon of polyploidy, with a special focus on the cotton genus.
Possible rotation projects include phylogenetic and phylogeographic studies in Echinacea and Hypericum, investigations of the consequences of gene and genome duplication in Gossypium, and mining EST resources in cotton for various purposes.
Our new 22,800 gene Affymetrix barley genome array
(http://barleypop.vrac.iastate.edu/BarleyBase/history.php) is being utilized to
conduct global expression profiling of disease resistance signaling pathways in the Triticeae (barley & wheat). 465 Barley1 GeneChip hybridizations representing 156 replicated barley-powdery mildew interactions and 63 hybridizations representing 15 stages in monocot development are available for analysis. BCB faculty Dickerson (Computer and Electrical Engineering). and, Nettleton (Statistics), are collaborating with the Wise group to analyze the array data and to build an interactive microarray database for gene expression in plants
(http://barleybase.org/). Rotation projects could include computational analysis of whole genome expression data, comparative analysis with the rice or Arabidopsis genomes, or analysis of pathways involved in disease resistance signaling.
(7/22/04)
I am in need of a BCB graduate student with expertise in computation and interests in microarray analysis. The project involves an integrated biocomputational approach to understand the factors that regulate seed development and composition. The practical consequence of this work is that it will impact our ability to use molecular technologies to direct plants, a biorenewable energy source, to accumulate large quantities of industrially-useful chemicals, and improve our food supply.
