<html><head><style type='text/css'>p { margin: 0; }</style></head><body><div style='font-family: arial,helvetica,sans-serif; font-size: 10pt; color: #000000'>Yuri Pritykin will present his preFPO on Friday December 6 at 1:30 PM <br>in Room 402. The members of his committee are: Mona Singh, advisor; <br>Olga Troyanskaya and Bernard Chazelle, readers; Tom Funkhouser and <br>Stanislav Shvartsman (CBE/Genomics), nonreaders. Everyone is invited <br>to attend his talk. His abstract follows below.<br><div style="color:#000;font-weight:normal;font-style:normal;text-decoration:none;font-family:Helvetica,Arial,sans-serif;font-size:12pt;">
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Title: Intermodular and intramodular proteins in protein interaction
networks<br>
<br>
The availability of large-scale protein-protein interaction networks
for numerous organisms provides an opportunity to comprehensively
analyze the roles proteins play in the functional organization of
the cell.<br>
<br>
First, we re-examine an influential but controversial
characterization of the dynamic modularity of the S. cerevisiae
interactome that incorporated gene expression data into network
analysis. We analyse the protein-protein interaction networks of
five organisms, S. cerevisiae, H. sapiens, D. melanogaster, A.
thaliana, and E. coli, and confirm significant and consistent
functional and structural differences between hub proteins that are
co-expressed with their interacting partners and those that are not,
and support the view that the former tend to be intramodular whereas
the latter tend to be intermodular. However, we also demonstrate
that in each of these organisms, simple topological measures are
significantly correlated with the average co-expression of a hub
with its partners, and therefore also reflect protein intra- and
inter- modularity. Further, cross-interactomic analysis demonstrates
that these simple topological characteristics of hub proteins tend
to be conserved across organisms. Overall, we give evidence that
purely topological features of static interaction networks reflect
aspects of the dynamics and modularity of interactomes as well as
previous measures incorporating expression data, and are a powerful
means for understanding the dynamic roles of hubs in interactomes.<br>
<br>
Second, we study the role of multifunctional genes (and proteins
they encode) in protein interaction networks. Many genes in a genome
have more than one function. However, genome-wide analysis of
multifunctional genes and an explanation of the mechanisms
underlying multifunctionality are still lacking. We leverage
functional annotations of genes to extract a group of genes each of
which has at least two completely different functions, and
distinguish these, the most multifunctional genes, from the
remaining genes that are currently known to have a single function.
We find biologically significant differences between multifunctional
and all other genes on a large scale. We show that multifunctional
genes are intermodular and play a central role in the interactome,
bridging different functional modules.<br>
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