Discovering hidden connections among diseases, genes and drugs based on microarray expression profiles with negative-term filtering.

ABSTRACT: Microarrays based on gene expression profiles (GEPs) can be tailored specifically for a variety of topics to provide a precise and efficient means with which to discover hidden information. This study proposes a novel means of employing existing GEPs to reveal hidden relationships among diseases, genes, and drugs within a rich biomedical database, PubMed. Unlike the co-occurrence method, which considers only the appearance of keywords, the proposed method also takes into account negative relationships and non-relationships among keywords, the importance of which has been demonstrated in previous studies. Three scenarios were conducted to verify the efficacy of the proposed method. In Scenario 1, disease and drug GEPs (disease: lymphoma cancer, lymph node cancer, and drug: cyclophosphamide)

SUBMITTER: Wu JS 

PROVIDER: S-EPMC4051596 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature