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Vesteinn Thorsson
Area of Expertise
Computational Biology
Current Position
Senior Research Scientist
Degree
Ph.D., Physics, Stony Brook University, 1992.
Research Interests
Dr. Thorsson's current area of interest is the use of global, whole-cell, measurement technologies such as DNA microarrays, proteomics, and phenotype arrays to elucidate mechanisms driving cellular processes. The aim is to provide researchers with tools to better utilize the power of such technologies in understanding biological networks. A powerful way to reveal network structure and function is through the use of perturbations, such as environmental changes and genetic manipulation. Examining gene expression changes and modification of phenotypes under such perturbations, we can assess our current understanding of a biological network, gain insight about novel interactions among network components, and provide predictive mathematical models describing these interactions. Dr. Thorsson has applied these methods to reveal regulatory networks structure in S. cerevisiae, Halobacterium NRC-1, and in mammalian macrophages.
Selected Publications
Bonneau R, Reiss DJ, Shannon P, Facciotti M, Hood L, Baliga NS, Thorsson V. The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo. 2006. Genome Biology 7: R36 (2006)
Thorsson V, Hörnquist M, Siegel AF, Hood L. Reverse Engineering Galactose Regulation in Yeast through Model Selection. 2005. Statistical Applications in Genetics and Molecular Biology 4(1) Art. 28.
Drees BL, Thorsson V, Carter GW, Rives AW, Raymond MZ, Avila-Campillo I, Shannon P, Galitski T. Derivation of genetic interaction networks from quantitative phenotype data. 2005. Genome Biol. 6(4) R38.
Ideker T, Thorsson V, Ranish JA, Christmas R, Buhler J, Bumgarner R, Aebersold R, Hood L. Integrated Genomic and Proteomic Analysis of a Systematically Perturbed Metabolic Network 2001. Science 292:929-934.
Ideker T, Thorsson V, Karp R. Discovery of Regulatory Interactions through Perturbation: Inference and Experimental Design. 2000. Pacific Symposium on Biocomputing 2000, Eds. R. B. Altman et al., World Scientific.
M. Gilchrist, V. Thorsson, B. Li, A. G. Rust, M. Korb, K. Kennedy, T. Hai, H. Bolouri and A. Aderem. Systems biology approaches identify ATF3 as a negative regulator of Toll-like receptor 4. Nature 441 (2006) 173-178.
Relevant Links
VERA and SAM: Finding significant expression differences in DNA microarray data
http://db.systemsbiology.net/software/VERAandSAM/
PhenotypeGenetics, a Cytoscape plug-in, constructs genetic-interaction networks from large sets of phenotype measurements from cells with single and pairwise genetic perturbations.
http://labs.systemsbiology.net/galitski/projs/system_genetics/protected/tutorial/index_pg.html
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