Graph-based identification of cancer signaling pathways from published gene expression signatures using PubLiME.

ABSTRACT: Gene expression technology has become a routine application in many laboratories and has provided large amounts of gene expression signatures that have been identified in a variety of cancer types. Interpretation of gene expression signatures would profit from the availability of a procedure capable of assigning differentially regulated genes or entire gene signatures to defined cancer signaling pathways. Here we describe a graph-based approach that identifies cancer signaling pathways from published gene expression signatures. Published gene expression signatures are collected in a database (PubLiME: Published Lists of Microarray Experiments) enabled for cross-platform gene annotation. Significant co-occurrence modules composed of up to 10 genes in different gene expression signatures are

SUBMITTER: Finocchiaro G 

PROVIDER: S-EPMC1874632 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature