BioContrasts: extracting and exploiting protein-protein contrastive relations from biomedical literature
Authors: Kim, Jung-jae; Zhang, Zhuo; Park, Jong C.; Ng, See-Kiong
Source: Bioinformatics, Volume 22, Number 5, 1 March 2006 , pp. 597-605(9)
Publisher: Oxford University Press
Key:
- Free Content
- New Content
- Subscribed Content
- Free Trial Content
Abstract:
Motivation: Contrasts are useful conceptual vehicles for learning processes and exploratory research of the unknown. For example, contrastive information between proteins can reveal what similarities, divergences and relations there are of the two proteins, leading to invaluable insights for better understanding about the proteins. Such contrastive information are found to be reported in the biomedical literature. However, there have been no reported attempts in current biomedical text mining work that systematically extract and present such useful contrastive information from the literature for exploitation.Results: Our BioContrasts system extracts protein-protein contrastive information from MEDLINE abstracts and presents the information to biologists in a web-application for exploitation. Contrastive information are identified in the text abstracts with contrastive negation patterns such as `A but not B'. A total of 799 169 pairs of contrastive expressions were successfully extracted from 2.5 million MEDLINE abstracts. Using grounding of contrastive protein names to Swiss-Prot entries, we were able to produce 41 471 pieces of contrasts between Swiss-Prot protein entries. These contrastive pieces of information are then presented via a user-friendly interactive web portal that can be exploited for applications such as the refinement of biological pathways.Availability: BioContrasts can be accessed at http://biocontrasts.i2r.a-star.edu.sg. It is also mirrored at http://biocontrasts.biopathway.orgSupplementary information: Supplementary materials are available at Bioinformatics online.Contact: skng@i2r.a-star.edu.sg; park@cs.kaist.ac.krKeywords: JEL classifications: F12, R12
Document Type: Research article
DOI: 10.1093/bioinformatics/btk016
Key:
- Free Content
- New Content
- Subscribed Content
- Free Trial Content


Click here for Page Help