Borislav Hristov will present his research seminar/general exam on Tuesday May 6 at 10AM in Room 402. The members of his committee are: Mona Singh (advisor), Olga Troyanskaya, and Tom Funkhouser. Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. ----- Original Message ----- Abstract: The improvement and the decreased cost of next generation DNA sequencing have enabled genome wide measurements in large numbers of individuals. This allows researchers to compare the genome variations in both healthy and sick individuals in order to help uncover the genetic underpinnings of human disease. However, complex diseases are caused by a combination of genetic perturbations- often the same phenotypic outcome (a disease case) can result from a different set of possible mutations, possibly in different loci. Cancer is a disease which exhibits such a great genetic heterogeneity. This makes studying it and identifying causal variants extremely difficult. We combine knowledge of biological interactions with genome sequencing data from The Cancer Genome Atlas to perform an integrated analysis of several types of cancer. Our hypothesis is that even though different patients could have entirely disjoint sets of somatic variants, these variants disturb similar cell processes and hence are closely connected in the biological network. We phrase the problem precisely in mathematical terms and devise an efficient greedy heuristic to solve it. We use a robust framework of cross validation tests to demonstrate the soundness of our approach. We are able to recover well known cancer genes as well as to highlight possible new ones. We show that our method yields both efficient and biologically relevant results. Reading List: Yona, Golan. Introduction to Computational Proteomics . CRC Press, 2011. Chapters: 1-7, 10, 13.2 Dand, Nick, et al. "BioGranat-IG: a network analysis tool to suggest mechanisms of genetic heterogeneity from exome-sequencing data." Bioinformatics 29.6 (2013): 733-741. Vandin, Fabio, Eli Upfal, and Benjamin J. Raphael. "Algorithms for detecting significantly mutated pathways in cancer." Journal of Computational Biology 18.3 (2011): 507-522. Ulitsky, Igor, et al. "DEGAS: de novo discovery of dysregulated pathways in human diseases." PLoS One 5.10 (2010): e13367. Navlakha, Saket, and Carl Kingsford. "The power of protein interaction networks for associating genes with diseases." Bioinformatics 26.8 (2010): 1057-1063. Wang, Peggy I., and Edward M. Marcotte. "It's the machine that matters: Predicting gene function and phenotype from protein networks." Journal of proteomics 73.11 (2010): 2277-2289. Gosline, Sara JC, et al. "SAMNet: a network-based approach to integrate multi-dimensional high throughput datasets." Integrative Biology 4.11 (2012): 1415-1427. Lee, Insuk, et al. "Prioritizing candidate disease genes by network-based boosting of genome-wide association data." Genome research 21.7 (2011): 1109-1121. Hofree, Matan, et al. "Network-based stratification of tumor mutations." Nature methods (2013). Jiang, Peng, and Mona Singh. "SPICi: a fast clustering algorithm for large biological networks." Bioinformatics 26.8 (2010): 1105-1111.