The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Automated extraction of information on protein–protein interactions from the biological literature
Open accessAbstract
Motivation: To understand biological process, we must clarify how proteins interact with each other. However, since information about protein–protein interactions still exists primarily in the scientific literature, it is not accessible in a computer-readable format. Efficient processing of large amounts of interactions therefore needs an intelligent information extraction method. Our aim is to develop an efficient method for extracting information on protein–protein interaction from scientific literature. Results: We present a method for extracting information on protein–protein interactions from the scientific literature. This method, which employs only a protein name dictionary, surface clues on word patterns and simple part-of-speech rules, achieved high recall and precision rates for yeast (recall \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \(=\) \end{document}86.8% and precision \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \(=\) \end{document}94.3%) and Escherichia coli (recall \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \(=\) \end{document}82.5% and precision \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \(=\) \end{document}93.5%). The result of extraction suggests that our method should be applicable to any species for which a protein name dictionary is constructed. Availability: The program is available on request from the authors. Contact: ono@otsuka.gr.jp * To whom correspondence should be addressed.
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KEGG: Kyoto Encyclopedia of Genes and Genomes
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Self-citationAutomatic extraction of biological information from scientific text: protein-protein interactions.
Blaschke, C., Andrade-Navarro, M. A., Ouzounis, C. A., & Valencia, A. (1999) · PubMed · Cited by 448
EcoCyc: Encyclopedia of Escherichia coli genes and metabolism
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Corpus annotation for mining biomedical events from literature
Kim, J.-D., Ohta, T., & Tsujii, J. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-10 · Cited by 395
Binding MOAD (Mother Of All Databases)
Hu, L., Benson, M. L., Smith, R. D., Lerner, M. G., & Carlson, H. A. (2005) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.20512 · Cited by 328
Donaldson, I., Martin, J., de Bruijn, B., Wolting, C., Lay, V., Tuekam, B., Zhang, S., Baskin, B., Bader, G. D., Michalickova, K., et al. (2003) · BMC Bioinformatics · doi:10.1186/1471-2105-4-11 · Cited by 340
Text mining and its potential applications in systems biology
Ananiadou, S., Kell, D. B., & Tsujii, J.-I. (2006) · Trends in Biotechnology · doi:10.1016/j.tibtech.2006.10.002 · Cited by 324
Motifs, modules and games in bacteria
Wolf, D. M., & Arkin, A. P. (2003) · Current Opinion in Microbiology · doi:10.1016/s1369-5274(03)00033-x · Cited by 303
Metadata
- Authors
- Ono, T., Hishigaki, H., Tanigami, A., & Takagi, T.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2001-02-01
- Volume
- 17
- Issue
- 2
- Pages
- 155-161
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2109070394
- Cited by
- 398
- References
- 13
- FWCI
- 8.03
- Type
- journal article
- Language
- en
- Open access
- bronze
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