An important aspect of the BCB training program is participation in Research Exploration Rotations. Participation in three research exploration rotations is required for all first year BCB students. The rotations serve several purposes:

• They are designed to help students choose their future major professors and to help professors choose graduate students;
• They provide students an opportunity to actively participate in research projects of BCB faculty laboratories; and
• They promote interaction and exchange of information among BCB research groups.

Selecting a Lab for Rotation

The selection of labs for rotations should be guided by the following:

• At least one rotation must be a "wet" laboratory experience (usually in a biological science laboratory using molecular biological, biophysical or biochemical techniques).
• At least one rotation must involve a strong computational component (usually in a research group in computer science, mathematics, physics, statistics or engineering).
• Students are strongly encouraged to participate in rotations in at least two different departments.

Faculty interested in having students rotate through their labs this Fall and in Spring, 2009, are below. Faculty who had rotations in the past are also listed. Links to their home pages are provided so you can become familiar with their on-going research projects. Some also have brief descriptions of potential rotation projects you might be involved with if you rotate in their labs.

Information on the research interests and links to all BCB faculty member's webpages can be found on our website at: http://www.bcb.iastate.edu/faculty/research.html.

Rotation Expectations

Because rotations are necessarily brief, students are not usually able to "complete" a project, in either a biological or computational research group. Instead, during the research exploration rotation period, students should:

• get to know the professor and the students and postdocs working in the research group;
• learn as much as possible about the professor's research projects;
• obtain "hands on" experience in one of the group's research projects;
• attend research group meetings and journal club meetings; and
• read reprints, reviews, and grant proposals related to the group's research.

It is appropriate for a rotating student to ask the rotation advisor whether the advisor would consider accepting him/her as a graduate student, but the final decision should not be made until all rotations have been completed.

Dates for Fall 2008/Spring 2009 Rotation Program

Forms to submit Rotation choices, evaluate your Rotations, and establish your Home Department

• Rotation Planning Form
• Rotation Evaluation Form
• Establishing Home Department Form

Adam Bogdanove, Plant Pathology

Rotation projects available center on 1) Reprogramming of host gene expression by bacterial pathogens of rice and 2) Comparative genomics of host and tissue-specificity in bacterial interactions with plants. Contact him to talk. (8/18/08)

Volker Brendel  Genetics, Development and Cell Biology

• Dr. Brendel's research - Algorithms for gene identification in genomic sequences; sequence alignment methods; transcriptional regulation; molecular phylogeny. He is accepting rotation students and invites interested students to visit his lab website for information about his research. (8/18/08)

Anne Bronikowski  Ecology, Evolution and Organismal Biology

• Dr. Bronikowski's research - 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

  Dr. Bronikowski is accepting rotation students, and invites interested students to visit her lab website for information about her research. (7/19/07)

Hui-Hsien Chou  Genetics, Development and Cell Biology and Computer Science

• Dr. Chou's research - Bioinformatics, Computational Biology and Artificial Life.

Dr. Chou will be on sabbatical leave after November, thus he cannot offer a formal rotation project this academic year. However, he welcomes new students to contact him for rotation opportunities if they are interested in his work. If possible, Dr. can arrange a rotation project that fits his schedule and yours. Another way to work with Dr. Chou is to subscribe to his BCB 596 Genomic Data Processing class, which will be offered in the Fall. (7/19/07)

Drena Dobbs  Genetics, Development and Cell Biology

Four BCB Rotation Projects - Fall 2008

• #1- Tools for cracking the protein-RNA recognition code: RNABindR & PRIDB

  Protein-RNA interactions play critical roles in many essential biological processes. We are developing tools to investigate the molecular recognition code that mediates protein-RNA interactions.

  Dobbs lab projects involve collaborations with Honavar & Jernigan groups, and include:

  1) design, implementation and evaluation of improved machine learning algorithms to predict RNA binding sites in proteins (& protein binding sites in RNAs); implement in our web-based server, RNABindR

  2) design and implementation of a new database, Protein-RNA Interface Database(PRIDB), a comprehensive resource for analysis, characterization and visualization of structurally-characterized RNA-protein complexes (database will be modeled after PPIDB, see URL below):

  Web Resources: RNABindR: http://bindr.gdcb.iastate.edu/RNABindR/

  PPIDB: http://ppidb.cs.iastate.edu/

  References: Terribilini M, Sander JD, Lee JH, Zaback P, Jernigan RL, Honavar V, Dobbs D. RNABindR: a server for analyzing and predicting RNA-binding sites in proteins. Nucleic Acids Res. 2007 May 5; [Epub ahead of print]

  http://nar.oxfordjournals.org/cgi/content/full/gkm294v1

  Preferred skills: Some computer programming ability & basic biology

• #2- Using structural information to re-engineer Zinc Finger DNA binding domains

  We are using both computational and wet-lab experiments to design DNA binding proteins that specifically recognize unique sequences in genomic DNA. Our server, Zinc Finger Targeter (ZiFiT), is designed to facilitate the modular design of ZFPs as well as the discovery of "rules" that govern protein-DNA interactions.

  Dobbs lab projects involve collaborations with Voytas, Miller and Honavar groups, and include:

  1) develop improved algorithms for site-specific ZFP design, e.g., by evaluating the use of structural information, in addition to sequence information

  2) analyze and develop algorithms for distinguishing ZFPs that bind DNA vs RNA vs protein

  3) develop high throughput DNA binding assays (e.g., SPR or microarray-based) to evaluate affinity & specificity of designed ZFPs

  Web Resources: http://bindr.gdcb.iastate.edu/ZiFiT

  http://www.zincfingers.org/

  Reference: Sander JD, Zaback P, Keith Joung J, Voytas DF, Dobbs D. Zinc Finger Targeter (ZiFiT): an engineered zinc finger/target site design tool. Nucleic Acids Res. 2007 May 25;

  http://nar.oxfordjournals.org/cgi/content/full/gkm349v1

  Preferred skills: Some computer programming ability & basic biology

• #3- Predicting structure and functional sites in the human telomerase RNP complex

  Telomerase is a ribonucleoprotein (RNP) enzyme that adds telomeric DNA repeat sequences to the ends of linear chromosomes. The enzyme plays pivotal roles in cellular senescence and aging, and because it provides a telomere maintenance mechanism for ~90% of human cancers, it is a promising target for cancer therapy. Despite its importance, a high-resolution structure of the telomerase enzyme has been elusive.

  Dobbs lab projects involve collaborations with Ho, Honavar and Jernigan groups, and include:

  1) using threading and homology modeling to predict the structure of the telomerase reverse transcriptase enzyme, including its protein components (hTERT & dyskerin) and its RNA component (hTERC).

  2) using machine learning algorithms to predict which residues in the hTERT protein interact with DNA, RNA and other proteins.

   Web Resources: http://www.genlink.wustl.edu/teldb/tel.html

  http://www4.utsouthwestern.edu/cellbio/shay-wright/intro/sw_intro.html

  Reference: Blackburn, EH, Greider, CW, and Szostak, JW Telomeres and telomerase: the path from maize, Tetrahymena and yeast to human cancer & aging Nature Medicine 12, 1133 - 1138 (2006).

  http://www.nature.com/doifinder/10.1038/nm1006-1133

  Preferred skills: Some computer programming ability & basic biology

• #4- Deciphering SNARE complex interactions in Arabidopsis (Bassham/Dobbs Rotation)

  Membrane fusion reactions within cells are catalyzed by members of the SNARE protein family and regulated by SM proteins. Expansion of the SNARE family in plants makes Arabidopsis a particularly attractive system for studying the specificity and functional specialization of SNARE family members. We are beginning to use computational modeling approaches, in conjunction with genetic and biochemical analyses, to investigate the mechanism and regulation of SNARE function and complex formation. Our overall goal is to understand how structural features of the SNARE proteins lead to specificity in membrane fusion pathways in vivo.

  This Bassham/Dobbs rotation project also involves collaborations with Honavar, Jernigan, and Ho groups. Specific projects include:

  1) computational structure prediction: homology modeling of helical bundle interactions required for SNARE-catalyzed membrane fusion and analysis/prediction of both structural and phenotypic effects of mutations on helix association and SNARE functional specificity

  2) machine learning: analysis and prediction of interactions between SM proteins and SNAREs in Arabidopsis; tools originally developed for prediction of MHC epitopes will be modified to investigate specific sequence and structural motifs that mediate specific SM-SNARE interactions

  Web Resources: PepMIL: http://ailab.cs.iastate.edu/PepMIL

  References: Chen Y, Y-K Shin and DC Bassham. 2005. YKT6 is a core constituent of membrane fusion machineries at the Arabidopsis trans-Golgi network. J Mol Biol 350:92-101.

  Preferred skills: Some computer programming ability & basic biology (8/15/08)

• You can find rotation information at her website at this address: http://rumi.gdcb.iastate.edu/ (8/16/07)

Rohan Fernando Animal Science

• Contact him to see if there is a rotation opportunity available. (8/15/08)

Mark Hargrove Biochemistry, Biophysics and Molecular Biology

• May have a Rotation opportunity. Please contact him. (8/15/08)

Vasant Honavar  Computer Science

• Rotation projects in Honavar's Lab
   
  Topic I:Algorithms and Software for Construction and Analysis of Gene and Protein Networks
   
  Collaboration involving: Dr. Vasant Honavar, Dr. Drena Dobbs, Dr. Heather Greenlee, Dr. Robert Jernigan and graduate students Cornelia Caragea, Fadi Towfic, Tim Alcon and post-doctoral associate Jae-Hyung Lee
   
  We are interested in analyzing mRNA and proteomics data in the context of other available information to elucidate gene and protein networks that orchestrate specific biological processes. Our group has developed a database and associated tools for construction and refinement of gene networks from disparate datasets. Retina Workbench, an instantiation of these tools, is being used in collaboration with Dr. Greenlee’s lab to construct models of gene and protein networks that control retinal differentiation. Work in progress is aimed at developing computational and statistical approaches to discovery of functional modules in gene and protein networks, and comparative analysis and integration of data from multiple experiments, multiple tissues, or multiple organisms.

  Web resources:

  http://www.cs.iastate.edu/~retinaworkbench/
   
  References:

  • Hecker, L., Alcon, T., Honavar, V., and Greenlee, H. Analysis and Interpretation of Large-Scale Gene Expression Data Sets Using a Seed Network. Journal of Bioinformatics and Biology Insights. Vol. 2. pp. 91-102, 2008.
  • Kohutyuk, O. (2007). Retina Workbench. MS Thesis. Computer Science.

  Topic II:Structural, physicochemical, and geometric characterization of macromolecular (protein-protein, protein-DNA, and protein-RNA) interfaces

  Collaborations involving:  Dr. Vasant Honavar, Dr. Drena Dobbs, Dr. Robert Jernigan, and graduate students Cornelia Caragea, Yasser El-Manzalawi, Michael Terribilini
   
  We have developed machine learning approaches to analysis and prediction of protein-protein, protein-DNA, protein-RNA interfaces from amino acid sequence (and whenever available), protein structure. We have also constructed comprehensive databases of protein-protein and protein-RNA interfaces. We are especially interested in characterization of structural and physicochemical characteristics of interfaces. Work in progress is aimed at developing reliable predictors of protein-protein and protein-nucleic acid interfaces.

  Web resources:

  http://ppidb.cs.iastate.edu/
  http://bindr.gdcb.iastate.edu/RNABindR/
  http://turing.cs.iastate.edu:8080/PredDNA/
  http://ailab.cs.iastate.edu/bcpred/ 

  References:

  • El-Manzalawy, Y., Dobbs, D., and Honavar, V. (2008) Predicting linear B-cell epitopes using string kernels. Journal of Molecular Recognition, DOI: 10.1002/jmr.893
  • Towfic, F., Caragea, C., Dobbs, D., and Honavar, V. (2008). Struct-NB: Predicting protein-RNA binding sites using structural features. International Journal of Data Mining and Bioinformatics, In press.
  • Caragea, C., Sinapov, J., Dobbs, D., and Honavar, V. (2007). Assessing the Performance of Macromolecular Sequence Classifiers, In: Proceedings of the IEEE Conference on Bioinformatics and Bioengineering (BIBE 2007). pp. 320-326, 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. doi:10.1093/nar/gkm294
  • Yan, C., Dobbs, D., Jernigan, R., and Honavar, V. (2007). Characterization of Protein-Protein Interfaces. The Protein journal. doi:10.1007/s10930-007-9108-x
  • Terribilini, M., Lee. J-H., Yan, C., Carpenter, S., Jernigan, R., Honavar, V. and Dobbs, D. Identifying interaction sites in recalcitrant proteins: predicted protein and rna binding sites in HIV-1 and EIAV agree with experimental data. Pacific Symposium on Biocomputing, Hawaii, World Scientific. Vol. 11. pp. 415-426, 2006.
  • Terribilini, M., Lee, J.-H., Yan, C., Jernigan, R. L., Honavar, V. and Dobbs, D. (2006). Predicting RNA-binding Sites from Amino Acid Sequence. In: RNA Journal.. Vol. 12. No. 1450. pp. 1462.
  • 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, 2006.
  • Sen, T.Z., Kloczkowski, A., Jernigan, R.L., Yan, C., Honavar, V., Ho, K-M., Wang, C-Z., Ihm, Y., Cao, H., Gu, X., and Dobbs, D. Predicting Binding Sites of Protease-Inhibitor Complexes by Combining Multiple Methods. BMC Bioinformatics. Vol. 5. pp. 205, 2004.
  • Yan, C., Dobbs, D., and Honavar, V. A Two-Stage Classifier for Identification of Protein-Protein Interface Residues. Bioinformatics. Vol. 20. pp. i371-378, 2004.

  Topic III: Machine learning approaches to functional annotation of proteins
   
  Collaboration involving: Dr. Vasant Honavar, Dr. Drena Dobbs, and graduate students Carson Andorf, Cornelia Caragea, Yasser El-Manzalawi, Oksana Yakhnenko
   
  We have been developing machine learning approaches to automated functional annotation of proteins. Carson Andorf has used these methods to discover potential errors in annotations of Mouse protein kinases in MGD. Work in progress is aimed at developing efficient, incrementally updatable predictive models for gene, protein, and genome annotation from large datasets. Of particular interest are methods for exploiting abstraction hierarchies over the input alphabet to construct accurate and robust predictors.
   
  Web resources:
  http://www.geneontology.org/meeting/go_users_2006_09_seattle/Honavar.ppt
    
  References:

  • Andorf, C., Dobbs, D. and Honavar, V. (2007). Exploring Inconsistencies in Genome Wide Protein Function Annotations: A Machine Learning Approach.BMC Bioinformatics 8:284 doi:10.1186/1471-2105-8-284
  • Yakhnenko, O., Silvescu, A., and Honavar, V. Discriminatively Trained Markov Model for Sequence Classification. IEEE Conference on Data Mining (ICDM 2005), Houston, Texas, IEEE Press, 2005.
  • Kang, D-K., Zhang, J., Silvescu, A., and Honavar, V. Multinomial Event Model Based Abstraction for Sequence and Text Classification. Proceedings of the Symposium on Abstraction, Reformulation, and Approximation (SARA 2005), Edinburgh, UK, Berlin: Springer-Verlag. Vol. 3607. pp. 134-148, 2005.

  Topic IV: Machine learning approaches to prediction of functional sites (e.g., phosphorylation sites, glycosylation sites, MHC peptide binding sites) in proteins.
   
  Collaboration involving: Dr. Vasant Honavar, Dr. Drena Dobbs, Yasser El-Manzalawi, Cornelia Caragea
   
  We have been developing machine learning methods for automated identification of functional sites in proteins. Work in progress is aimed at further improving existing machine learning methods and developing new methods as needed for reliable prediction of functionally important sites in proteins and to leverage the resulting predictions in developing more accurate models of macromolecular networks responsible for specific biological processes.

  Web resources:
  http://ailab.cs.iastate.edu/PepMIL/
  http://turing.cs.iastate.edu/EnsembleGly/
  http://ailab.cs.iastate.edu/bcpred/

  References:

  • El-Manzalawy, Y., Dobbs, D., and Honavar, V. (2008). Predicting Flexible Length Linear B-cell Epitopes, 7th International Conference on Computational Systems Bioinformatics, Stanford, CA. Singapore: World Scientific. In press.
  • El-Manzalawy, Y., Dobbs, D., and Honavar, V. (2008) Predicting linear B-cell epitopes using string kernels. Journal of Molecular Recognition, DOI: 10.1002/jmr.893
  • Caragea, C., Sinapov, J., Silvescu, A., Dobbs, D. And Honavar, V. (2007). Glycosylation Site Prediction Using Ensembles of Support Vector Machine Classifiers. BMC Bioinformatics. doi:10.1186/1471-2105-8-438.

  Project V: AnexDB: Animal Gene Expression Database and Associated Analysis Tools
   
  Collaboration involving Dr. Vasant Honavar and Dr. Chris Tuggle and graduate students Oliver Couture and Neeraj Koul
   
  We are developing an animal gene expression database and associated tools for querying and analysis of data from gene expression analysis experiments. Work in progress is aimed at extending the current implementation of AnexDB to facilitate further analysis of gene expression datasets from different experiments e.g., by leveraging and contributing to tools being developed in Honavar’s lab for construction and analysis of gene and protein networks.

  Web resources:

  http://www.anexdb.org/
  http://www.cs.iastate.edu/~retinaworkbench/

  Publications:

  Check with Drs. Honavar and Tuggle for preprints or drafts.

  Project VI: Bioinformatics Tools for Comparative Analysis of Animal Phenotype Data

  Collaboration involving Dr. Vasant Honavar and Dr. Jim Reecy and graduate students

  We have been developing computational tools for collaborative construction of phenotype ontologies for agriculturally as well as clinically important species. Such ontologies play an important role in comparative analysis and integration of data from multiple species.

  Web resources:

  http://www.animalgenome.org/bioinfo/projects/ATO/

  Publications:

  • Hughes, LaRon, Bao, J., Honavar, V., and Reecy, J. (2008). Animal Trait Ontology (ATO): the importance and usefulness of a unified trait vocabulary for animal species. Journal of Animal Science, 86:1485-1491.
  • Bao, J., Hu, Z., Caragea, D., Reecy, J., and Honavar, V. 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. (8/15/08)

Richard Honzatko Biochemistry, Biophysics and Molecular Biology

• May have a Rotation opportunity. Contact him. (8/15/08)

Fred Janzen Ecology, Evolution and Organismal Biology

• May have a rotation opportunity. Contact him. (8/15/08)

Dennis Lavrov Ecology, Evolution and Organismal Biology

• We are interested in understanding the early evolution of animals from both phylogenetic and functional perspectives.  Several rotation opportunities are available in our group:
  
  1) Phylogenetic reconstruction of animal relationships based on mitochondrial and cDNA data;
  2) Software development for the analysis of gene order data;
  3) Sponge cDNA exploration and annotation
  
  If you are interested in any of these projects or if you have some other ideas, send me an email (dlavrov@iastate.edu) and come to chat. (7/19/08)

Allen Miller, Plant Pathology

• Bioinformatical opportunities in my lab involve RNA structure and function:  from structure of eukaryotic mRNAs in protein synthesis, to plant viral phylogenetic analysis.
• RNA is a good macromolecule to do bioinformatics with because its structure is a lot easier to predict than protein, thanks to Watson-Crick base pairing. But thanks to non-Watson-Crick tertiary interactions, it's unpredictable enough to make it challenging (and a lot more fun than DNA). Also RNA can be an enzyme and the genetic material at the same time. How cool is that?

1.  We have discovered a novel structure in which the 5' and 3' untranslated regions (UTRs) of a plant virus mRNA must base pair (by forming "kissing stem-loops") to facilitate translation initiation.   Similar interactions may exist in some human viruses.   I'd like a bioinformatics student to search mRNA databases to seek host and viral mRNAs (from plants to humans) that may have similar long-distance base pairing interactions.   If successful, and backed up by experimental evidence, this could lead to a very significant publication.

2.  Another project involves building and curating a database of plant viral sequences and mining them for interesting stuff.   Papers guaranteed from this project (but not necessarily from the rotation alone).

3.  Also, work with a structural biology student to predict RNA 3D structure, based on phylogenetic conservation and known structural data. In my lab, enthusiasm, curiosity and drive are most important. (7/23/07)

Basil Nikolau  Biochemistry, Biophysics and Molecular Biology

• Nikolau's research is focused on the functional genomics of metabolism; the discovery and charcaterization of new gene functions using system based approaches; integrating genomics, transcript profiling, proteomics and metabolomics. Several opportunities are available in the group, particularly in the development of bioinformatics tools for metabolomics research, recetly funded by NSF and DOE. If you are interested, drop me an email and come to chat. (8/15/08)

James Reecy Animal Science

• Contact him to set up a rotation opportunity. He will provide projects for publication on this page, soon. Watch for them. (8/22/08)

Guang Song Computer Science

Our research goals are to understand the mechanism of biological systems and functions, especially the dynamic processes of how they take place. We are interested in studying: how proteins fold; ligand migration pathways; how proteins change conformations upon ligand binding, to name a few. We design computational models and simulation programs to study, simulate, and understand biological processes. Here are some possible projects:

• Protein Dynamics In this project, you will have a chance to study the
  effects of crystal packing on protein dynamics using elastic network models.
  This will be an extension of work I did on vGNM model (Journal of Molecular
  Biology. Vol. 369, pp. 880-93, 2007). Specifically, you will investigate how
  crystal packing may suppress some internal vibrations of a protein molecule
  and influence its external rigid body motion within the crystal environment.
• Allostery communication - How proteins make conformation changes upon ligand
  binding? In this project, the student will use several possible models to
  study the conformation changes in proteins, and how the conformation change at
  one site is communicated to a distant site.
• Molecular Dynamics simulations one interesting project would be to use MD
  simulation to study protein transition pathways. This is an important topic
  since much can be learned about a proteins functional mechanism if we know
  its transition pathways. (8/15/08)

Xueyu Song  Chemistry

• I anticipate I can take one rotational student with chemistry background. I also have the grant money to support the student if s/he would like to work on our project on the theory of protein crystallization. (8/15/08)

Alex Travesset  Physics

• I anticipate an opening for a graduate student on computational studies of different families of GTPases proteins with phospholipids (more concretely, phosphoinositides) in cell membranes. The study will also include a characterization of the dynamics of the signalling pathways that result from such interactions. Interested students should not hesitate to contact me at trvsst@ameslab.gov (8/15/08)

Christopher Tuggle  Animal Science

• Dr. Tuggle's research - Genomic and molecular genetic approaches to understanding the control of gene expression; bioinformatics analysis of microarray data to find the transcriptional response to infection, in developmental processes, and in appetite control. He is accepting BCB students for rotations, to work on one of the following rotation projects that are part of collaborative group (Tuggle, Honavar, Dekkers, Nettleton, Anderson) efforts in functional genomics that includes a full-time programmer and several graduate students:
  
  1) We are developing a database and associated tools to store and analyze data from approximately 150 current and 200 additional future Affymetrix Genechip experiments. We need help to develop the PHP/Java scripting for visualization and querying the database to pull out biologically relevant answers.
  
  2) We are also developing a web interface between the above database and on-campus and off-campus users of our Affymetrix data. We need someone to contribute to improvements in the PHP/Java to database interface, especially in streamlining and improving the useability of the interface for users.
  
  Please email him at cktuggle@iastate.edu or phone 515-294-4252 for further information. (8/8/07)

Nicole Valenzuela, Ecology, Environment, and Organismal Biology

• My research program focuses on the integrative study of the ecological (proximate) and evolutionary (ultimate) processes that explain the origin and persistence of sex determining mechanisms in vertebrates. This integrative approach requires investigating the development of the sexual phenotype from several perspectives spanning classical ecology to modern evolutionary and ecological genomics, and at several levels of biological organization. See my website for more information on our research areas ( http://www.public.iastate.edu/~nvalenzu/). At the moment, rotation opportunities in my lab include the bioinformatic analysis of multiple genes related to sex differentiation across turtles and other taxa. Interested students with computational skills can contact me for further details. (8/15/08)

Steve Whitham  Plant Pathology

My research program involves the functional genomics analysis of plant-microbe interactions. The projects that we have integrate genomic sequence information, novel high throughput functional genomics tools for soybean, extensive mRNA expression profiling data sets, and massively parallel sequencing to identify the regulatory networks that control responses of soybean plants to environmental stresses.

We have several goals including:

• Identification of promoter elements that regulate defense gene networks
• Characterization and functional analysis of transcription factor families associated with defense gene networks
• Assembly and annotation of 454 sequence from plant pathogens or infected plant tissues
• Identification of pathogen proteins that modify the functions of plant proteins
• Integrating information on sequence, gene expression, and function (based on experimentation) into a database

Students are encouraged to contact me by email or phone to discuss possible rotation projects. (8/15/08)

Roger Wise  Plant Pathology

• Research in the Wise laboratory is focused on the functional analysis of important agronomic genes in cereal crops. We are actively involved in high-throughput GeneChip studies to analyze the interactions among plants and plant pathogens. Visit his website and these: http://wiselab.org/, http://barleybase.org/, and http://plexdb.org/ to learn more about his research. (7/20/07)

• Dr. Wurtele's Research - Metabolic networking; evolution of biotin-containing enzymes; methods for analysis and visualization of high throughput data; development of the Meta!Blast cell videogame. She is accepting rotation students, and invites interested students to visit her lab website for information about her research.
  
  Two opportunities are available in her group:
  
  Regulatory and metabolic networks
  Biological aim- identify genes that control composition and metabolic flux in yeast and E. coli
  Informatics goal- Develop approaches to combine multiple types of high-throughput data within the MetNet database graph model of a biological network.

  Funding- National Science Foundation
  
  
  Development of novel capabilities for Meta!Blast, an open-Sg-based video game focused on cell structure and metabolic biology
  Biological aim- Work with a team of biologists, teachers, artists, and computer scientists to create a state of the art biology video game targeted at high school and university students.
  Informatics goal- Develop and program approaches to visualize changes in cellular structures and support player-game environment interactions.

  Funding- National Institute of Health (8/15/08)