Aaron Wong will present his research seminar/general exam on Tuesday May 11 at 2PM in Room 402. The members of his committee are: Olga Troyanskaya (advisor), Mona Singh, and Andrea LaPaugh. 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. ---------------------------------- Abstract ----------------------------- A comparative analysis of heterogenous biological networks across diverse organisms With the advent of modern sequencing technologies, high-throughput genomics data are being generated in diverse organisms. Historically, we leveraged these data to construct a single biological network for each organism by integrating heterogeneous datasets spanning thousands of experiments. These integrated functional networks are fully-connected, where each node represents a gene and edge weights describe the probability that a pair of genes participate in a similar biological process. Thus, each network attempts to capture the available experimental data in a particular organism and predict gene-function relationships. As barriers to entry lower, we will have increasingly more genomics data for more diverse organisms. There is great interest in comparing the genomes of different organisms, illuminating the evolutionary processes that have shaped their genomes. In this study, we use a previously described method that extends networks of gene relationships to maps of gene function and construct functional maps in two organisms. We use Gene Ontology to classify genes into functional groups and compare the network properties of these gene groups across functional networks. We attempt to characterize patterns of functional evolution by comparing network cohesiveness of functional groups, identifying both conserved and divergent biological processes. Further, we describe inter-process relationships, conserved among functional maps, to identify patterns of co-regulation between processes. ----------------------------- Book: [1] Artificial Intelligence: A Modern Approach (Second Edition) by Stuart Russell and Peter Norvig - section V (Uncertain knowledge and reasoning), section VI (Learning) Papers: [1] Alter, O., P. O. Brown, and D. Botstein, 2003 Generalized singular value decomposition for comparative analysis of genome-scale expression data sets of two different organisms. Proc Natl Acad Sci U S A 100: 3351-3356. [2] Kriston L. McGary, Tae Joo Park, John O. Woods, Hye Ji Cha, John B. Wallingford, and Edward M. Marcotte, Proc Natl Acad Sci USA Systematic discovery of non-obvious human disease models through orthologous phenotypes [3] Gandhi, T. K., J. Zhong, S. Mathivanan, L. Karthick, et al., 2006 Analysis of the human protein interactome and comparison with yeast, worm and fly interaction datasets. Nat Genet 38: 285-293. [4] Goh, K. I., M. E. Cusick, D. Valle, B. Childs, et al., 2007 The human disease network. Proc Natl Acad Sci U S A 104: 8685-8690. [5] Huttenhower, C., and O. G. Troyanskaya, 2006 Bayesian data integration: a functional perspective. Comput Syst Bioinformatics Conf 341-351. [6] Huttenhower, C., E. M. Haley, M. A. Hibbs, V. Dumeaux, et al., 2009 Exploring the human genome with functional maps. Genome Res 19: 1093-1106. [7] Myers, C. L., D. R. Barrett, M. A. Hibbs, C. Huttenhower, and O. G. Troyanskaya, 2006 Finding function: evaluation methods for functional genomic data. BMC Genomics 7: 187. [8] Sharan, R., S. Suthram, R. M. Kelley, T. Kuhn, et al., 2005 Conserved patterns of protein interaction in multiple species. Proc Natl Acad Sci U S A 102: 1974-1979. [9] Storey, J. D., and R. Tibshirani, 2003 Statistical significance for genomewide studies. Proc Natl Acad Sci U S A 100: 9440-9445. [10] Watts, D. J., and S. H. Strogatz, 1998 Collective dynamics of 'small-world' networks. Nature 393: 440-442.