Output details
11 - Computer Science and Informatics
University of Manchester
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Output 0 of 0 in the submission
Article title
BioContext: an integrated text mining system for large-scale extraction and contextualization of biomolecular events
Type
D - Journal article
Title of journal
Bioinformatics
Article number
-
Volume number
28
Issue number
16
First page of article
2154
ISSN of journal
1460-2059
Year of publication
2012
URL
-
Number of additional authors
3
Additional information
<28> Contextualisation of bio-text mining results (e.g. linking extracted interactions to specific species, anatomical locations or underlying diseases) is critical for their usefulness. This paper is significant as it is one of the first attempts to place text-mined results into biological context, systematically exploring the usefulness of large-scale processing of full-text literature in biology. The extracted data is open, and has been used to support efficient knowledge curation, e.g. for pain research in Pfizer (wiki-pain.org, benjamin.sidders@pfizer.com).
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
1
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
