Direct use of information extraction from scientific text for modeling and simulation in the life sciences
| Published date | 20 November 2009 |
| Pages | 505-519 |
| Date | 20 November 2009 |
| DOI | https://doi.org/10.1108/07378830911007637 |
| Author | Martin Hofman‐Apitius,Erfan Younesi,Vinod Kasam |
| Subject Matter | Information & knowledge management,Library & information science |
Direct use of information
extraction from scientific text for
modeling and simulation in the
life sciences
Martin Hofman-Apitius, Erfan Younesi and Vinod Kasam
Department of Bioinformatics,
Fraunhofer Institute for Algorithms and Scientific Computing (SCAI),
Sankt Augustin, Germany
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 modern 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.
Keywords Information research, Modelling, Life sciences
Paper type Research paper
1. Introduction
The Life Sciences (biology, biochemistry, medicine) are still dominated by empirical
observations. Because of this empirical nature of the life sciences there is a flood of
descriptive publications in this domain. Besides a remarkable increase in the
complexity of the scientific content of life science publications (e.g. observations that
cross the borders of traditional disciplines, indicated by new journals with names such
as NATURE Chemical Biology), the number of journals is also growing fast.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0737-8831.htm
Direct use of
information
extraction
505
Received 23 June 2009
Revised 2 July 2009
Accepted 24 July 2009
Library Hi Tech
Vol. 27 No. 4, 2009
pp. 505-519
qEmerald Group Publishing Limited
0737-8831
DOI 10.1108/07378830911007637
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