Helmholtz Gemeinschaft

Search
Browse
Statistics
Feeds

Caipirini: using gene sets to rank literature

[img] PDF (Article) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
497kB
[img] Other (Supplementary Information)
30kB

Item Type:Article
Title:Caipirini: using gene sets to rank literature
Creators Name:Soldatos, T.G. and O'Donoghue, S.I. and Satagopam, V.P. and Barbosa-Silva, A. and Pavlopoulos, G.A. and Wanderley-Nogueira, A.C. and Soares-Cavalcanti, N.M. and Schneider, R.
Abstract:BACKGROUND: Keeping up-to-date with bioscience literature is becoming increasingly challenging. Several recent methods help meet this challenge by allowing literature search to be launched based on lists of abstracts that the user judges to be 'interesting'. Some methods go further by allowing the user to provide a second input set of 'uninteresting' abstracts; these two input sets are then used to search and rank literature by relevance. In this work we present the service 'Caipirini' (http://caipirini.org) that also allows two input sets, but takes the novel approach of allowing ranking of literature based on one or more sets of genes. RESULTS: To evaluate the usefulness of Caipirini, we used two test cases, one related to the human cell cycle, and a second related to disease defense mechanisms in Arabidopsis thaliana. In both cases, the new method achieved high precision in finding literature related to the biological mechanisms underlying the input data sets. CONCLUSIONS: To our knowledge Caipirini is the first service enabling literature search directly based on biological relevance to gene sets; thus, Caipirini gives the research community a new way to unlock hidden knowledge from gene sets derived via high-throughput experiments.
Source:BioData Mining
ISSN:1756-0381
Publisher:BioMed Central (U.K.)
Volume:5
Number:1
Page Range:1
Date:1 February 2012
Official Publication:https://doi.org/10.1186/1756-0381-5-1
PubMed:View item in PubMed

Repository Staff Only: item control page

Downloads

Downloads per month over past year

Open Access
MDC Library