KID--an algorithm for fast and efficient text mining used to automatically generate a database containing kinetic information of enzymes.

BMC Bioinformatics
Stephanie HeinenDietmar Schomburg

Abstract

The amount of available biological information is rapidly increasing and the focus of biological research has moved from single components to networks and even larger projects aiming at the analysis, modelling and simulation of biological networks as well as large scale comparison of cellular properties. It is therefore essential that biological knowledge is easily accessible. However, most information is contained in the written literature in an unstructured way, so that methods for the systematic extraction of knowledge directly from the primary literature have to be deployed. Here we present a text mining algorithm for the extraction of kinetic information such as K(M), K(i), k(cat) etc. as well as associated information such as enzyme names, EC numbers, ligands, organisms, localisations, pH and temperatures. Using this rule- and dictionary-based approach, it was possible to extract 514,394 kinetic parameters of 13 categories (K(M), K(i), k(cat), k(cat)/K(M), V(max), IC(50), S(0.5), K(d), K(a), t(1/2), pI, n(H), specific activity, V(max)/K(M)) from about 17 million PubMed abstracts and combine them with other data in the abstract. A manual verification of approx. 1,000 randomly chosen results yielded a recall between 51% and...Continue Reading

References

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Citations

Jul 4, 2012·Bioinformatics·Darby Tien-Hao ChangJung-Hsien Chiang
Nov 30, 2011·BMC Bioinformatics·Rafael CarreiraAnália Lourenço
Feb 26, 2013·Briefings in Bioinformatics·Chen LiDietrich Rebholz-Schuhmann
Jun 1, 2011·Molecular Informatics·Miguel VazquezAlfonso Valencia

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Software Mentioned

AMENDA
FRENDA
RK
Qt4
BRENDA
Kinetikon
KMedDB
IUPAC
SABIO
kinetic

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