A transversal approach to predict gene product networks from ontology-based similarity.

ABSTRACT:

Background

Interpretation of transcriptomic data is usually made through a "standard" approach which consists in clustering the genes according to their expression patterns and exploiting Gene Ontology (GO) annotations within each expression cluster. This approach makes it difficult to underline functional relationships between gene products that belong to different expression clusters. To address this issue, we propose a transversal analysis that aims to predict functional networks based on a combination of GO processes and data expression.

Results

The transversal approach presented in this paper consists in computing the semantic similarity between gene products in a Vector Space Model. Through a weighting scheme over the annotations, we take into account the representativ

SUBMITTER: Chabalier J 

PROVIDER: S-EPMC1940024 | biostudies-literature | 2007 Jul

REPOSITORIES: biostudies-literature