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Direct use of information extraction from scientific text for modeling and simulation in the life sciences

 
: Hofmann-Apitius, M.; Younesi, E.; Kasam, V.

:

Höppner, M.:
"Upgrading the eLibrary: Enhanced information services driven by technology and economics" : Proceedings of the 9th International Bielefeld Conference, Bielefeld, Germany, 3 - 5 February 2009
Bingley: Emerald, 2009 (Library hi tech 27.2009, Nr.4)
ISSN: 0737-8831
pp.505-519
International Bielefeld Conference <9, 2009, Bielefeld>
English
Conference Paper, Journal Article
Fraunhofer SCAI ()
text mining; information extraction; in silico experiment; drug discovery; grid computing

Abstract
Purpose - The purpose of this paper is to demonstrate how the information extracted from scientific text can be directly used in support of life science research projects, In modem digital-based research and academic libraries, librarians should be able to support data discovery and organization of digital entities in order to foster research projects effectively; thus the paper aims to speculate that text mining and knowledge discovery tools could be of great assistance to librarians. Such tools simply enable librarians to overcome increasing complexity in the number as well as contents of scientific literature, especially in the emerging interdisciplinary fields of science. This paper seeks to present an example of how evidences extracted from scientific literature can be directly integrated into in silico disease models in support of drug discovery projects. Design/methodology/approach - The application of text-mining as well as knowledge discovery tools is explained in the form of a knowledge-based workflow for drug target candidate identification. Moreover, an in silico experimentation framework is proposed for the enhancement of efficiency and productivity in the early steps of the drug discovery workflow. Findings - The in silico experimentation workflow has been successfully applied to searching for hit and lead compounds in the World-wide In Silico Docking On Malaria (WISDOM) project and to finding novel inhibitor candidates. Practical implications - Direct extraction of biological information from text will ease the task of librarians in managing digital objects and supporting research projects. It is expected that textual data will play an increasingly important role in evidence-based approaches taken by biomedical and translational researchers. Originality/value - The proposed approach provides a practical example for the direct integration of text- and knowledge-based data into life science research projects, with the emphasis on their application by academic and research libraries in support of scientific projects.

: http://publica.fraunhofer.de/documents/N-118808.html