Bayesian Bi-Clustering Approach for the Identification of Pathway-Modulating Genes Using Biomedical Literature Search with Ontology Fingerprint

• Activity Number: 177
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
• Sponsor: ENAR
• Author(s): Dongjun Chung* and Andrew B. Lawson
• Companies: Medical University of South Carolina and Medical University of South Carolina
• Keywords: bi-clustering ; biomedical literature search ; gene ontology ; bioinformatics

Abstract

Biological pathways are the de facto functional unit for studying biology at the system level. Discovering new players and mechanisms of pathway modulation is critical to understand the mechanisms of pathway regulation and to identify the novel targets for therapeutics. While biomedical literature search has been considered as a powerful approach to investigate pathway-modulating genes, majority of these approaches, based on the co-occurrence of genes within the biomedical literature, are limited by the fact that large proportion of abstracts only contains information for a single gene. Recently, the concept of ontology fingerprint was proposed to overcome such limitation by utilizing gene ontology information for the biomedical literature search and this approach was shown to be effective to investigate the relationship among genes. In this presentation, we propose a novel Bayesian bi-clustering approach which extends the idea of ontology fingerprint and facilitates gene clustering and easier interpretation within a unified framework. We evaluate the proposed approach with an application to the studies of pathway-modulating genes in yeast.