A dictionary to identify small molecules and drugs in free text

K.M. Hettne, R.H. Stierum, M.J. Schuemie, P.J.M. Hendriksen, B.J.A. Schijvenaars, E.M. van Mulligen, J. Kleinjans, J.A. Kors

    Research output: Contribution to journalArticleAcademicpeer-review

    90 Citations (Scopus)

    Abstract

    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.
    Original languageEnglish
    Pages (from-to)2983-2991
    JournalBioinformatics
    Volume25
    Issue number22
    DOIs
    Publication statusPublished - 2009

    Keywords

    • biomedical text
    • chemical names
    • chemistry
    • information
    • database
    • abbreviations
    • system
    • identification
    • knowledgebase
    • recognition

    Fingerprint Dive into the research topics of 'A dictionary to identify small molecules and drugs in free text'. Together they form a unique fingerprint.

    Cite this