[talks] A Wong general exam

Melissa Lawson mml at CS.Princeton.EDU
Wed May 5 15:57:51 EDT 2010

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.

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


[1] Artificial Intelligence: A Modern Approach (Second Edition) by
Stuart Russell and Peter Norvig
- section V (Uncertain knowledge and reasoning), section VI (Learning)


[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
[6] Huttenhower, C., E. M. Haley, M. A. Hibbs, V. Dumeaux, et al.,
2009 Exploring the human genome with functional maps. Genome Res 19:
[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.

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