[talks] T Yue general exam

Melissa Lawson mml at CS.Princeton.EDU
Tue May 5 09:22:27 EDT 2009

Tao Yue will present his research seminar/general exam on Monday May 11 at 10AM in room
The members of his committee are:  Mona Singh, advisor, Olga Troyanskaya, and Tom
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.


Sequence similarity has long been used to find orthologs between proteins in
different species, or to find paralogs within a species.  Predictions of
these evolutionary relationships can be exploited to infer and transfer
functional annotations between proteins.

In the past decade, high-throughput screening techniques have enabled the
construction of protein interaction networks for many model organisms.  In
addition to direct protein interactions, other associations can also be made
between pairs of proteins: coexpression, phylogenetic, neighborhood, gene
fusion, etc.  Such networks provide the opportunity to characterize a
protein not just by its sequence, but by its interaction and association

This talk explains how to exploit these networks to detect functionally
similar proteins between different species.  Such networks, particularly the
protein interaction networks, provide more direct evidence of function than
does sequence similarity.  We evaluate the power of various metrics for
uncovering functionally similar proteins without using sequence similarity.
In addition, we apply Rankprop, a diffusion-based process that has
previously been used on sequence similarity, to these networks.  We show
that the use of networks from multiple organisms yields improvements in
precision and recall.  Furthermore, this procedure can be used to
disambiguate predictions made by sequence-based methods, as well as correct

These techniques show promising applications as more interaction data
becomes available.  They also have potential future applications to the
detection of analogous proteins, i.e., those that evolved the same function
independently and thus lack sequence similarity.


Mount, Bioinformatics: Sequence and Genome Analysis.  Cold Spring Harbor
Laboratory Press, 2004.  Chapters 1-7, 11.

PAPERS: General area: Protein networks

Barabasi and Oltvai, Network Biology: Understanding the Cell's Functional
Organization.  Nature Reviews Genetics, February 2004, 101-113.

Nabieva and Singh, Protein function prediction via analysis of interactomes.
Prediction of Protein Structures, Functions, and Interactions (ed J.
Bujnicki), 2009.

Zhu et al, Getting connected: analysis and principles of biological
networks.  Genes & Developmnent 21 (2007): 1010-1024.

PAPERS: Subareas

Bandyopadhyay et al.  Systematic identification of functional orthologs
based on protein network comparison.  Genome Research 16 (2006), pp.

Li et al.  OrthoMCL: Identification of Ortholog Groups for Eukaryotic
Genomes.  Genome Research 13 (2003), pp. 2178-2189.

Remm et al.  Automatic Clustering of Orthologs and In-paralogs from Pairwise
Species Comparisons.  J. Molecular Biology (2001) 314, pp. 1041-1052.

Sharan et al.  Conserved patterns of protein interaction in multiple
species.  PNAS, February 8, 2005, 1974-1979.

Sharan and Ideker.  Modeling cellular machinery through biological network
comparison.  Nature Biotechnology 24 (2006), 427-433.

Singh et al.  Global alignment of multiple protein interaction networks with
application to functional orthology detection.  PNAS, September 2, 2008, pp.

Yosef et al.  Improved Network-based Identification of Protein Orthologs.
Bioinformatics Vol. 24 ECCB 2008, pp. i200-i206.

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