Prof. Irit Gat

Dep. of Cell Research and Immunology
מח חקר התא ואימונולוגיה סגל אקדמי בכיר
Prof. Irit Gat
Phone: 03-6406945
Office: Britannia-Porter, 209

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.


Recent Publications

Mazza A1, Gat-Viks I, Sharan R. Elucidating Influenza Inhibition Pathways via Network Reconstruction. J Comput Biol. 2014 Jan 22.


Mazza A, Gat-Viks I, Farhan H, Sharan R. A minimum-labeling approach for reconstructing protein networks across multiple conditions. Algorithms Mol Biol. 2014 Feb 9;9(1):1.


Altboum Z 1 , Steuerman Y , David E , Barnett-Itzhaki Z , Valadarsky L , Keren-Shaul H , Meningher T , Mendelson E , Mandelboim M , Gat-Viks I , Amit I . Digital cell quantification identifies global immune cell dynamics during influenza infection. Mol Syst Biol. 2014 Feb 28;10(2):720


Irit Gat-Viks, Nicolas Chevrier, Roni Wilentzik, Thomas Eisenhaure, Raktima Raychowdhury, Yael Steuerman, Alex K Shalek, Nir Hacohen, Ido Amit & Aviv Regev: Deciphering molecular circuits from genetic variation underlying transcriptional responsiveness to stimuli. Nature Biotechnology, 2013, doi:10.1038/nbt.2519


Kirby A, Gnirke A, Jaffe DB, Baresova V, Pochet N, Blumenstiel B, Ye C, Aird D, Stevens C, Robinson JT, Cabili MN, Gat-Viks I, Kelliher E, Daza R, Defelice M, Hulkova H, Sovova J, Vylet'al P, Antignac C, Guttman M, Handsaker RE, Perrin D, Steelman S, Sigurdsson S, Scheinman SJ, Sougnez C, Cibulskis K, Parkin M, Green T, Rossin E, Zody MC, Xavier RJ, Pollak MR, Alper SL, Lindblad-Toh K, Gabriel S, Hart PS, Regev A, Nusbaum C, Kmoch S, Bleyer AJ, Lander ES, Daly MJ. Mutations causing medullary cystic kidney disease type 1 lie in a large VNTR in MUC1 missed by massively parallel sequencing. Nature Genetics. 2013 Mar;45(3):299-303. doi: 10.1038/ng.2543. Epub 2013 Feb 10.


Granit RZ, Gabai Y, Hadar T, Karamansha Y, Liberman L, Waldhorn I, Gat-Viks I, Regev A, Maly B, Darash-Yahana M, Peretz T, Ben-Porath I. EZH2 promotes a bi-lineage identity in basal-like breast cancer cells. Oncogene. 2012 Sep 17. doi: 10.1038/onc.2012.390. [Epub ahead of print]


Chevrier N, Mertins P, Artyomov MN, Shalek AK, Iannacone M, Ciaccio MF, Gat-Viks I, Tonti E, DeGrace MM, Clauser KR, Garber M, Eisenhaure TM, Yosef N, Robinson J, Sutton A, Andersen MS, Root DE, von Andrian U, Jones RB, Park H, Carr SA, Regev A, Amit I, Hacohen N. Systematic discovery of TLR signaling components delineates viral-sensing circuits. Cell. 2011 Nov 11;147(4):853-67.


Szczurek E, Markowetz F, Gat-Viks I, Biecek P, Tiuryn J, Vingron M: Deregulation upon DNA damage revealed by joint analysis of context-specific perturbation data. BMC bioinformatics 2011, 12:249.


Ziv-Ukelson M, Gat-Viks I, Wexler Y, Shamir R: A faster algorithm for simultaneous alignment and folding of RNA. Journal of computational biology : a journal of computational molecular cell biology 2010, 17(8):1051-1065.


Gat-Viks I, Meller R, Kupiec M, Shamir R: Understanding gene sequence variation in the context of transcription regulation in yeast. PLoS genetics 2010, 6(1):e1000800. [software]


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.


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.


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. [software]


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.


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.


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.[software]


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.


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.


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.


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.


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.


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.


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.


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.


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.


I Gat-Viks, R Sharan and R Shamir (2003). Scoring clustering solutions by their biological relevance. Bioinformatics 19: 2381-2389.


Tel Aviv University makes every effort to respect copyright. If you own copyright to the content contained
here and / or the use of such content is in your opinion infringing, Contact us as soon as possible >>