Journal Article

A dictionary to identify small molecules and drugs in free text

Kristina M. Hettne, Rob H. Stierum, Martijn J. Schuemie, Peter J. M. Hendriksen, Bob J. A. Schijvenaars, Erik M. van Mulligen, Jos Kleinjans and Jan A. Kors

in Bioinformatics

Volume 25, issue 22, pages 2983-2991
Published in print November 2009 | ISSN: 1367-4803
Published online September 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp535
A dictionary to identify small molecules and drugs in free text

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Motivation: From the scientific community, a lot of effort has been spent on the correct identification of gene and protein names in text, while less effort has been spent on the correct identification of chemical names. Dictionary-based term identification has the power to recognize the diverse representation of chemical information in the literature and map the chemicals to their database identifiers.

Results: We developed a dictionary for the identification of small molecules and drugs in text, combining information from UMLS, MeSH, ChEBI, DrugBank, KEGG, HMDB and ChemIDplus. Rule-based term filtering, manual check of highly frequent terms and disambiguation rules were applied. We tested the combined dictionary and the dictionaries derived from the individual resources on an annotated corpus, and conclude the following: (i) each of the different processing steps increase precision with a minor loss of recall; (ii) the overall performance of the combined dictionary is acceptable (precision 0.67, recall 0.40 (0.80 for trivial names); (iii) the combined dictionary performed better than the dictionary in the chemical recognizer OSCAR3; (iv) the performance of a dictionary based on ChemIDplus alone is comparable to the performance of the combined dictionary.

Availability: The combined dictionary is freely available as an XML file in Simple Knowledge Organization System format on the web site http://www.biosemantics.org/chemlist.

Contact: k.hettne@erasmusmc.nl

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  7929 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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