Ph.D.:	Tel Aviv University, Tel Aviv, Israel, 2004
Phone:	(Office) +972-3-640-6945
E-mail:	iritgv@post.tau.ac.il
Room#:	208-209

Personal Information

. My personal website is http://igatviks.lifesci.mytau.org/lab/

Research Interests

My group develops computational systems biology approaches to tackle a major problem in medicine: to reveal the molecular mechanisms underlying the basis of complex disease. We broadly pursuit two goals:

• Use genomic knowledge to understand how signal transduction, transcriptional control and other molecular factors underlie autoimmune and infectious disease, and

• Understand how DNA variations in the genomes of individuals shape their complex disease phenotypes.

Our aim is to map and quantitatively characterize this complex cellular immune response, to extend our understanding of heritable disease susceptibility, and eventually, to devise biomarkers for diagnosis and personalize therapeutics. To that end, we develop computational methods in statistics, probabilistic modeling, and bioinformatics, and work in a close collaboration with experimental labs to design and perform high-throughput experiments. Our research is stimulated by new technologies, and we employ genome-wide data such as microarrays, nanostring and sequencing, with advanced methods in learning and statistics.

Selected Publications

1. S Shapira, I Gat-Viks, B Shum, A Dricot, M de Grace, PB Gupta, T Hao, SJ Silver, DE Root, DE Hill, A Regev, N Hacohen (2009). A physical and regulatory map of host-influenza interactions reveals pathways in H1N1 infection. Cell 139:1255-1267.
2. I Gat-Viks, R Meller, M Kupiec, R Shamir (2009). Understanding gene sequence variation in the context of transcription regulation in yeast. PLoS Genetics, In Press.
3. AJ Bass, H Watanabe, S Yu, CH Mermel, S Perner, RG Verhaak, SY Kim, L Wardwell, P Tamayo, I Gat-Viks et al (2009). SOX2 is an amplified lineage-survival oncogene in lung and esophageal squamous cell carcinomas. Nature Genetics 41:1238-1242.
4. E Szczurek, I Gat-Viks, J Tiuryn and M Vingron (2009). Elucidating regulatory mechanisms downstream of a signaling pathway using informative experiments. Nature Molecular Systems Biology 5:287.
5. I Gat-Viks and M Vingron (2009). Evidence for gene-specific rather than transcription rate-dependent histone H3 exchange in yeast coding regions. PLoS Computational Biology 5(2):e1000282.
6. M Ziv-Ukelson, I Gat-Viks, Y Wexler and R Shamir (2008). A non-heuristic speedup of the Sankoff-85 algorithm. Lecture Notes in Bioinformatics 5251, Springer, Berlin.
7. I Ulitsky, I Gat-Viks and R Shamir (2008). MetaReg: a platform for modeling, analysis and visualization of biological systems using large-scale experimental data. Genome Biology 2: 9(1):R1.
8. I Gat-Viks and R Shamir (2007). Refinement and expansion of signaling pathways: the osmotic response network in yeast. Genome Research 17(3): 358-67.
9. I Gat-Viks, R Shamir, RM Karp and R Sharan (2006). Reconstructing chain functions in genetic networks. SIAM Journal of Discrete Mathematics 20: 727-740.
10. I Gat-Viks, A Tanay, D Raijman and R Shamir (2005). A probabilistic methodology for integrating knowledge and experiments on biological networks. Journal of Computational Biology 13(2): 165-81.
11. I Gat-Viks, A Tanay, D Raijman and R Shamir (2005). Factor graph network models for biological systems. Proc. RECOMB 2005, Boston, NY pp. 31-47, Lecture Notes in Bioinformatics 3500, Springer, Berlin.
12. I Gat-Viks, A Tanay and R Shamir (2004). Biological networks involving metabolic pathways and gene regulation: modeling and inference. The first RECOMB satellite meeting on regulatory genomics, University of California, San Diego, March 26-27, 2004. E. Eskin, C. Workman (Eds.): RECOMB 2004 workshop on Regulatory Genomics, LNBI 3318, pp. 98–113, 2005. Springer-Verlag Berlin Heidelberg.
13. I Gat-Viks, A Tanay and R Shamir (2004). Modeling and analysis of heterogeneous regulation in biological network. Journal of Computational Biology 11(6): 1034-49.
14. I Gat-Viks, R Shamir, RM Karp and R Sharan (2004). Reconstructing chain functions in genetic networks. Proc. Pacific Symposium on Biocomputing (PSB 04) pp. 498-509.
15. A Tanay, I Gat-Viks and R Shamir (2004). A global view of the selection forces in the evolution of yeast cis-regulation. Genome Research 14: 829-834.
16. I Gat-Viks and Ron Shamir (2003). Chain functions and scoring functions in genetic networks. Proc. 11th International Conference on Intelligent Systems for Molecular Biology (ISMB 03), Brisbane, Australia, July 2003. Bioinformatics S19: i108--i117.
17. I Gat-Viks, R Sharan and R Shamir (2003). Scoring clustering solutions by their biological relevance. Bioinformatics 19: 2381-2389.