Literature based discovery of gene clusters using phylogenetic methods

Biomedical literature can offer valuable information for organizing genes associated with the etiology and pathogenesis of disease. In this study, we demonstrate the utility of existing phylogenetic methods for organizing 375 genes associated with Breast Cancer using the MeSH annotations from over 35,000 Medline articles. Specifically, we compare the clustering (using the Colless Imbalance Index, Ic) of distance-based methods, which are used by popular phylogenetic clustering algorithms, and a character- based method (Maximum Parsimony) that is commonly used for phylogenetic studies. Focusing on genes that cluster around BRCA1 and BRCA2, we examine the relevance of the clustered genes proposed by the different clustering methods based on the number of exclusive MeSH terms. Our results indicate that existing phylogenetic methods and associated metrics can be used for organizing genes according to annotated knowledge in biomedical literature.