Czarnecki, Jan and Shepherd, Adrian J. (2016) Metabolic pathway mining. In: Keith, J.M. (ed.) Bioinformatics Volume II: Structure, Function, and Applications. Methods in Molecular Biology 1526. New York, U.S.: Humana Press, pp. 139-158. ISBN 9781493966110.
Abstract
Understanding metabolic pathways is one of the most important fields in bioscience in the post-genomic era, but curating metabolic pathways requires considerable man-power. As such there is a lack of reliable, experimentally verified metabolic pathways in databases and databases are forced to predict all but the most immediately useful pathways. Text-mining has the potential to solve this problem, but while sophisticated text-mining methods have been developed to assist the curation of many types of biomedical networks, such as protein–protein interaction networks, the mining of metabolic pathways from the literature has been largely neglected by the text-mining community. In this chapter we describe a pipeline for the extraction of metabolic pathways built on freely available open-source components and a heuristic metabolic reaction extraction algorithm.
Metadata
| Item Type: | Book Section |
|---|---|
| Additional Information: | Series ISSN: 1064-3745 |
| Keyword(s) / Subject(s): | Metabolic pathway, Metabolic interaction extraction, Text-mining, Natural language processing, Named entity recognition, Information extraction |
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Natural Sciences |
| Research Centres and Institutes: | Data Analytics, Birkbeck Institute for |
| Depositing User: | Administrator |
| Date Deposited: | 07 Mar 2017 16:59 |
| Last Modified: | 02 Aug 2023 17:30 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/17762 |
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