Extensions to eGIFT Allowing Text-mining of Gene Lists

Schmidt, Carl J.

Date: Sunday, January 15, 2012
Time: 8:20 AM

Room: Pacific Salon 6-7 (2nd Floor)

Carl J. Schmidt , University of Delaware, Newark, DE

Catalina Oana Tudor Tudor , University of Delaware, Newark, DE

A.S.M.Ashique Mahmood , University of Delaware, Newark, DE

Cecilia Arighi , University of Delaware, Newark, DE

K. Vijay-Shanker , University of Delaware, Newark, DE

Cathy H. Wu , University of Delaware, Newark, DE

Shurnevia J. Strickland , University of Delaware, Newark, DE

eGIFT is a gene centric system for surveying biological literature with two major applications: 1: Helping annotators find articles describing gene function; 2: Helping scientists evaluate high-throughput experiments by extracting information relevant to genes in their lists. eGIFT identifies informative terms (iTERMS), which are statistically enriched words found in abstracts about a given gene. We have extended eGIFT to allow analysis of gene lists to identify iTERMS common to multiple genes in a list. These enriched iTERMS can provide insight into the biology affected by the input genes. In addition, the abstracts used to generate the iTERMs can be passed to RLIMS-P, a text-mining program designed to extract information relevant to phosphorylation. Together, the iTERMS and RLIMS-P provide useful outputs for hypothesis generation. We will discuss these tools in the context of transcriptome data examining cardiac hypertrophy.

W518 Extensions to eGIFT Allowing Text-mining of Gene Lists