*biointelligence                               25th feb  2010

Pandora, a PAthway and Network DiscOveRy Approach based on common biological
evidence*


Many biological phenomena involve extensive interactions between many of the
biological pathways present in cells. However, extraction of all the
inherent biological pathways remains a major challenge in systems biology.
With the advent of high-throughput functional genomic techniques, it is now
possible to infer biological pathways and pathway organization in a
systematic way by integrating disparate biological information.

Results: Here, we propose a novel integrated approach that uses network
topology to predict biological pathways. We integrated four types of
biological evidence (protein–protein interaction, genetic interaction,
domain–domain interaction and semantic similarity of Gene Ontology terms) to
generate a functionally associated network. This network was then used to
develop a new pathway finding algorithm to predict biological pathways in
yeast. Our approach discovered 195 biological pathways and 31 functionally
redundant pathway pairs in yeast. By comparing our identified pathways to
three public pathway databases (KEGG, BioCyc and Reactome), we observed that
our approach achieves a maximum positive predictive value of 12.8% and
improves on other predictive approaches. This study allows us to reconstruct
biological pathways and delineates cellular machinery in a systematic view.

Availability: The method has been implemented in Perl and is available for
downloading from http://www.oicr.on.ca/research/ouellette/pandora. It is
distributed under the terms of GPL (
http://opensource.org/licenses/gpl-2.0.php)

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Team Biointelligence

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