Table of Contents Author Guidelines
Advances in Bioinformatics
Volume 2012, Article ID 509126, 12 pages
Research Article

BioEve Search: A Novel Framework to Facilitate Interactive Literature Search

1Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA
2Department of Computer Science and Engineering, Arizona State University, Tempe, AZ 85281, USA
3Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA

Received 15 November 2011; Revised 7 March 2012; Accepted 28 March 2012

Academic Editor: Jin-Dong Kim

Copyright © 2012 Syed Toufeeq Ahmed et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background. Recent advances in computational and biological methods in last two decades have remarkably changed the scale of biomedical research and with it began the unprecedented growth in both the production of biomedical data and amount of published literature discussing it. An automated extraction system coupled with a cognitive search and navigation service over these document collections would not only save time and effort, but also pave the way to discover hitherto unknown information implicitly conveyed in the texts. Results. We developed a novel framework (named “BioEve”) that seamlessly integrates Faceted Search (Information Retrieval) with Information Extraction module to provide an interactive search experience for the researchers in life sciences. It enables guided step-by-step search query refinement, by suggesting concepts and entities (like genes, drugs, and diseases) to quickly filter and modify search direction, and thereby facilitating an enriched paradigm where user can discover related concepts and keywords to search while information seeking. Conclusions. The BioEve Search framework makes it easier to enable scalable interactive search over large collection of textual articles and to discover knowledge hidden in thousands of biomedical literature articles with ease.