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Ralph Ackerman

Education: Ph.D., Florida, 1975

Research Interests: Mathematical biology, environmental physiology, sex determination

• Mathematical Biology, Computational Modeling, and Metabolic and Developmental Networking --Mathematical biology; modeling environmental physiology; sex determination

Description: Current Research: 1) Water exchange by Reptile Eggs during incubation; 2) Temperature Dependent Sex Determination

Research in my laboratory is directed toward analyzing and understanding two processes: 1) transport processes involving the exchange of energy and materials within the organism and between the organism and the environment and 2) biological regulatory processes. Interest in these processes is directed toward understanding how the organism is adapted to its environment. The approach is typically interdisciplinary and employs both theoretical and experimental techniques to generate and test hypotheses. The current direction of activity in the laboratory is toward describing and understanding the environmental physiology of vertebrate embryos, especially reptile and bird embryos.

Vita: Click here to download

Website: Ralph Ackerman

Dean Adams

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

Research Interests:

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

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

Selected Publications:

• Adams, D.C. 2008. Phylogenetic meta-analysis. Evolution. 62:567-572.

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

Vita:Click here to download

Website: Dean Adams

Srinivas Aluru

Education: Ph.D., Iowa State, 1994

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

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

Selected Publications:

• P. Ko and S. Aluru, "Space efficient linear time construction of suffix arrays," Journal of Discrete Algorithms, to appear.
• S. J. Emrich, S. Aluru and P.S. Schnable, "Status of maize genome sequencing and assembly projects," AgBiotechNet Journal, to appear.
• P. Ko, M. Narayanan, A. Kalyanaraman, and S. Aluru, "Space-conserving optimal DNA-protein alignment," IEEE Computational Systems Bioinformatics Conference, to appear.
• S. J. Emrich, S. Aluru, Y. Fu, T.J. Wen, M. Narayanan, L. Guo, D.A. Ashlock, and P.S. Schnable, "A Strategy for Assembling the Maize (Zea mays L.) Genome," Bioinformatics, Vol. 20, No. 2, pp. 140-147, 2004.
• S. Rajko and S. Aluru, "Space and time optimal parallel sequence alignments," IEEE Transactions on Parallel and Distributed Systems, Vol. 15, No. 11, 2004.
• S. Aluru, "Suffix Trees and Suffix Arrays," in Handbook of Data Structures and Applications, edited by Sartaj Sahni and Dinesh P. Mehta, CRC Press, 2004.
• S. J. Emrich, S. Aluru, Y. Fu, T.J. Wen, M. Narayanan, L. Guo, D.A. Ashlock, and P.S. Schnable, "A strategy for assembling the maize genome," Plant and Animal Genomes Conference Bioinformatics Workshop, 2004.

Vita: Click here to download

Website: Srinivas Aluru

Amy Andreotti

Education: Ph.D., Princeton, 1994

Research Interests: Macromolecular structure-function, NMR spectroscopy

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

Description:

Selected Publications:

• Min, L., Fulton, D.B. and Andreotti, A.H. (2005) A case study of proline isomerization in cell signaling. Front. Biosci. 10, 385-397.
• Andreotti, A.H. (2003) Native state proline isomerization: an intrinsic molecular switch. Biochemistry 42, 9515-9524.
• Laederach, A., Cradic, K.W., Brazin, K.N., Zamoon, J., Fulton, D.B., Huang, X.Y. and Andreotti, A.H. (2002) Competing modes of self-association in the regulatory domains of Bruton's tyrosine kinase: intramolecular contact versus asymmetric homodimerization. Protein Sci. 11, 36-45.
• Laederach, A., Andreotti, A.H. and Fulton, D.B. (2002) Solution and micelle-bound structures of tachyplesin I and its active aromatic linear derivatives. Biochemistry 41, 12359-12368.
• Watson, R.M., Woody, R.W., Lewis, R.V., Bohle, D.S., Andreotti, A.H., Ray, B. and Miller, K.W. (2001) Conformational changes in pediocin AcH upon vesicle binding and approximation of the membrane-bound structure in detergent micelles. Biochemistry 40, 14037-14046.

Vita: Click here to download

Website: Amy Andreotti

Lyric Bartholomay

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

Research Interests:

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

Selected Publications:

Vita: Click here to download

Website: New Faculty

William Beavis

Education:

Research Interests:

Selected Publications:

Vita: Click here to download

Website: New Faculty

Madan Bhattacharyya

Education: Ph.D., Western Ontario, 1987

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

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

Description: The primary interest of the Bhattacharyya lab is to understand the molecular basis of plant-pathogen interactions

Selected Publications:

• Gao, H., Narayanan, N., Ellison, L., and Bhattacharyya M.K. (2005) Two classes of highly similar coiled coil-nucleotide binding-leucine rich repeat genes isolated from the Rps1-k locus encode Phytophthora resistance in soybean. . Mol. Plant-Microbe Interact., 18:1035-1045.      
• Sandhu, D., Schallock K.G., Rivera-Velez, N., Lundeen, P., Cianzio, S., and Bhattacharyya, M.K. (2005) Soybean Phytophthora resistance gene Rps8 maps closely to the Rps3 region. . J. Heredity, 96: 536-541.      
• Bhattacharyya, M.K., Narayanan, N. N., Gao, H., Salimath, S.S., Santra, D., Ellison, L., Kasuga, T., Liu, Y., Espinosa, B., Marek, L.F., Shoemaker, R.C., Gijzen, M. and Buzzell, R.I. (2005)Identification of a large cluster of coiled coil-nucleotide binding site-leucine rich repeat-type genes from the Rps1 region containing Phytophthora resistance genes in soybean. Theor. Appl. Genet., 111: 75-86.      
• Sandhu, D., Gao, H., Cianzio, S., and Bhattacharyya, M.K. (2004)Deletion of a Disease Resistance Nucleotide-Binding-Site Leucine-Rich- Repeat-like Sequence Is Associated With the Loss of the Phytophthora Resistance Gene Rps4 in Soybean. Genetics 168: 2157-2167      
• W-M. Chou, T. Shigaki, C. Dammann, Y-Q. Liu, M. K. Bhattacharyya (2004). Inhibition of Phosphoinositide-Specific Phospholipase C Results in the Induction of Pathogenesis-Related Genes in Soybean. Plant Biol 6: 664-672.    

Vita: Click here to download

Website: Madan Bhattacharyya

Adam Bogdanove

Education: Ph.D., Cornell, 1997

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

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

Description:

Selected Publications:

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

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

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.

Website: Volker Brendel

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

Steve Cannon

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

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

BCB Research Areas:

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

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

Selected Publications:

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

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

Vita: Click here to download

Website: Steven Cannon

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

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.

Department Website: Hui-Hsien Chou

Dianne Cook

Education: Ph.D., Rutgers, 1993

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

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

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

Selected Publications:

• 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

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

Jack Dekkers

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

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

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

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

Selected Publications:

• 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.
• Dekkers, J.C.M., and F. Hospital. 2002. Utilization of molecular genetics in genetic improvement of plants and animals. Nature Reviews: Genetics 3: 22-32.
•  Zhao, H.H., R.L. Fernando, and J.C.M. Dekkers. 2007. Power and precision of alternate methods for linkage disequilibrium mapping of QTL. Genetics: 175: 1975-1986.
• Habier, D., R.L. Fernando, J.C.M. Dekkers. 2007. The impact of relationship information genome-assisted breeding values. Genetics 177: 23892397

Vita: Click here to download

Website: Jack Dekkers

Julie Dickerson

Education: Ph.D., USC, 1993

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

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

Description:

Selected Publications:

• 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

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

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

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

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

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

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

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

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

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

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

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

Vasant Honavar

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

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

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

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

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

Selected Publications:

• 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

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

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

Xiaoqiu Huang

Education: Ph.D., Penn State, 1990

Research Interests: Computational problems in genome sequencing and analysis

• Bioinformatics-- Computational problems in genome sequencing and analysis

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

Selected Publications:

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

Vita: Click here to download

Website: Xiaoqiu Huang

Fred Janzen

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)
• Schwanz, L. E., and F. J. Janzen. 2008. Climate change and temperature-dependent sex determination: can individual plasticity in nesting phenology prevent extreme sex ratios? Physiological and Biochemical Zoology 81:accepted pending revision.
• St. Juliana, J. R., and F. J. Janzen. 2007. Can natural phenotypic variances be estimated reliably under homogeneous laboratory conditions? Journal of Evolutionary Biology 20:1406-1414.

Vita: Click here to download

Website: Fred Janzen

Robert Jernigan

Education: Ph.D., Stanford, 1967

Research Interests: Computational structural biology and bioinformatics

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

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

• 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

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

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

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.

Website: Susan Lamont

Dennis Lavrov

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

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

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

Description:

Selected Publications:

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

Vita: Click here to download

Website: Dennis Lavrov

Carolyn Lawrence

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

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

Selected Publications:

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

Website: Carolyn Lawrence

Howard Levine

Education: Ph.D., Cornell, 1969

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

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

Selected Publications:

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

Vita: Click here to download

Website: Howard Levine

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.

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

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

Roger Maddux

Education: Ph.D., Berkeley, 1978

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

• Mathematical Biology-- species-area relationships

Description:

Selected Publications:

Vita: Click here to download

Website: Roger Maddux

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

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

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

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

How cells decode the genetic code

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

Sustainable control of crop diseases and pests

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

Selected Publications:

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

Vita: Click here to download

Website: W. Allen Miller

Chris Minion

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

Research Interests: Microbial pathogenomics, gene regulation

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

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

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

Selected Publications:

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