Mining experimental evidence of molecular function claims from the literature.

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  • Author(s): Crangle CE;Crangle CE; Cherry JM; Hong EL; Zbyslaw A
  • Source:
    Bioinformatics (Oxford, England) [Bioinformatics] 2007 Dec 01; Vol. 23 (23), pp. 3232-40. Date of Electronic Publication: 2007 Oct 17.
  • Publication Type:
    Journal Article; Research Support, N.I.H., Extramural
  • Language:
    English
  • Additional Information
    • Source:
      Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE
    • Publication Information:
      Original Publication: Oxford : Oxford University Press, c1998-
    • Subject Terms:
      Artificial Intelligence* ; Natural Language Processing* ; Periodicals as Topic*; Evidence-Based Medicine/*methods ; Information Storage and Retrieval/*methods ; Saccharomyces cerevisiae Proteins/*classification ; Saccharomyces cerevisiae Proteins/*metabolism; Reproducibility of Results ; Sensitivity and Specificity
    • Abstract:
      Motivation: The rate at which gene-related findings appear in the scientific literature makes it difficult if not impossible for biomedical scientists to keep fully informed and up to date. The importance of these findings argues for the development of automated methods that can find, extract and summarize this information. This article reports on methods for determining the molecular function claims that are being made in a scientific article, specifically those that are backed by experimental evidence.
      Results: The most significant result is that for molecular function claims based on direct assays, our methods achieved recall of 70.7% and precision of 65.7%. Furthermore, our methods correctly identified in the text 44.6% of the specific molecular function claims backed up by direct assays, but with a precision of only 0.92%, a disappointing outcome that led to an examination of the different kinds of errors. These results were based on an analysis of 1823 articles from the literature of Saccharomyces cerevisiae (budding yeast).
      Availability: The annotation files for S.cerevisiae are available from ftp://genome-ftp.stanford.edu/pub/yeast/data_download/literature_curation/gene_association.sgd.gz. The draft protocol vocabulary is available by request from the first author.
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    • Grant Information:
      R03 LM009752 United States LM NLM NIH HHS; P41HG02273 United States HG NHGRI NIH HHS; P41 HG001315-16 United States HG NHGRI NIH HHS; R43 HG003600 United States HG NHGRI NIH HHS; P41 HG002273 United States HG NHGRI NIH HHS; 2P41HG001315 United States HG NHGRI NIH HHS; P41 HG001315 United States HG NHGRI NIH HHS; R43CAHG003600-01 United States PHS HHS; P41 HG002273-11 United States HG NHGRI NIH HHS
    • Accession Number:
      0 (Saccharomyces cerevisiae Proteins)
    • Publication Date:
      Date Created: 20071019 Date Completed: 20071221 Latest Revision: 20211020
    • Publication Date:
      20231215
    • Accession Number:
      PMC3041023
    • Accession Number:
      10.1093/bioinformatics/btm495
    • Accession Number:
      17942445