BioTextQuest: a web-based biomedical text mining suite for concept discovery

BioTextQuest combines automated discovery of significant terms in article clusters with structured knowledge annotation, via Named Entity Recognition services, offering interactive user-friendly visualization. A tag-cloud-based illustration of terms labeling each document cluster are semantically an...

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Bibliographic Details
Published in:Bioinformatics 2011-12, Vol.27 (23), p.3327-3328
Main Authors: Papanikolaou, Nikolas, Pafilis, Evangelos, Nikolaou, Stavros, Ouzounis, Christos A., Iliopoulos, Ioannis, Promponas, Vasilis J.
Format: Article
Language:English
Subjects:
Algorithms
Animals
Biological and medical sciences
Cluster Analysis
Data Mining
Drosophila - embryology
Drosophila - genetics
Fundamental and applied biological sciences. Psychology
General aspects
Internet
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Natural Language Processing
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Summary:BioTextQuest combines automated discovery of significant terms in article clusters with structured knowledge annotation, via Named Entity Recognition services, offering interactive user-friendly visualization. A tag-cloud-based illustration of terms labeling each document cluster are semantically annotated according to the biological entity, and a list of document titles enable users to simultaneously compare terms and documents of each cluster, facilitating concept association and hypothesis generation. BioTextQuest allows customization of analysis parameters, e.g. clustering/stemming algorithms, exclusion of documents/significant terms, to better match the biological question addressed. Availability: http://biotextquest.biol.ucy.ac.cy Contact: vprobon@ucy.ac.cy; iliopj@med.uoc.gr Supplementary Information: Supplementary data are available at Bioinformatics online.
ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btr564