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

Abstract

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.