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Bioinformatics. 2011 Jul 1;27(13):i111-9. doi: 10.1093/bioinformatics/btr214.

Discovering and visualizing indirect associations between biomedical concepts.

Author information

1
School of Information Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, Japan. tsuruoka@jaist.ac.jp

Abstract

MOTIVATION:

Discovering useful associations between biomedical concepts has been one of the main goals in biomedical text-mining, and understanding their biomedical contexts is crucial in the discovery process. Hence, we need a text-mining system that helps users explore various types of (possibly hidden) associations in an easy and comprehensible manner.

RESULTS:

This article describes FACTA+, a real-time text-mining system for finding and visualizing indirect associations between biomedical concepts from MEDLINE abstracts. The system can be used as a text search engine like PubMed with additional features to help users discover and visualize indirect associations between important biomedical concepts such as genes, diseases and chemical compounds. FACTA+ inherits all functionality from its predecessor, FACTA, and extends it by incorporating three new features: (i) detecting biomolecular events in text using a machine learning model, (ii) discovering hidden associations using co-occurrence statistics between concepts, and (iii) visualizing associations to improve the interpretability of the output. To the best of our knowledge, FACTA+ is the first real-time web application that offers the functionality of finding concepts involving biomolecular events and visualizing indirect associations of concepts with both their categories and importance.

AVAILABILITY:

FACTA+ is available as a web application at http://refine1-nactem.mc.man.ac.uk/facta/, and its visualizer is available at http://refine1-nactem.mc.man.ac.uk/facta-visualizer/.

CONTACT:

tsuruoka@jaist.ac.jp.

PMID:
21685059
PMCID:
PMC3117364
DOI:
10.1093/bioinformatics/btr214
[Indexed for MEDLINE]
Free PMC Article

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