A dictionary to identify small molecules and drugs in free text

• Published in: Bioinformatics 2009-11, Vol.25 (22), p.2983-2991
• Main Authors: Hettne, Kristina M., Stierum, Rob H., Schuemie, Martijn J., Hendriksen, Peter J. M., Schijvenaars, Bob J. A., Mulligen, Erik M. van, Kleinjans, Jos, Kors, Jan A.
• Format: Article
• Language: English
• Subjects: abbreviations; Abstracting and Indexing as Topic - methods; Biological and medical sciences; biomedical text; chemical names; chemistry; Computational Biology - methods; Dictionaries as Topic; Dictionaries, Chemical; Fundamental and applied biological sciences. Psychology; General aspects; identification; information; Information Storage and Retrieval - methods; knowledgebase; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Natural Language Processing; Pharmaceutical Preparations - chemistry; recognition; Software; system; Unified Medical Language System
• ISSN: 1367-4803; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btp535

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: [e-mail] Supplementary information: Supplementary data are available at Bioinformatics online.