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Automated extraction of information in molecular biology
Author(s) -
Andrade Miguel A.,
Bork Peer
Publication year - 2000
Publication title -
febs letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.593
H-Index - 257
eISSN - 1873-3468
pISSN - 0014-5793
DOI - 10.1016/s0014-5793(00)01661-6
Subject(s) - computational biology , extraction (chemistry) , biology , computer science , evolutionary biology , chemistry , chromatography
We review data mining techniques in molecular biology, specifically those that extract information from the scientific literature itself. As more of the biological literature is published electronically, there is an opportunity, and even a need, to automatically summarize the literature in a customized way, for example by associating keywords to a topic. These keywords can be extracted from relevant publications. The process of keyword extraction can be automated and optimized to keep literature pointers automatically up‐to‐date or to filter relevant information from the literature. To illustrate these points, OMIM (Online Mendelian Inheritance in Man), a database of human inherited diseases, was linked to the literature and keywords were derived that covered distinct aspects such as genetic information on the one hand and disease‐specific protein and phenotypic information on the other. They were used to extract information that is helpful for keeping entries about disease up‐to‐date.