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Journal of Integrative Bioinformatics

Editor-in-Chief: Schreiber, Falk / Hofestädt, Ralf

Managing Editor: Sommer, Björn

Ed. by Baumbach, Jan / Chen, Ming / Orlov, Yuriy / Allmer, Jens

Editorial Board: Giorgetti, Alejandro / Harrison, Andrew / Kochetov, Aleksey / Krüger, Jens / Ma, Qi / Matsuno, Hiroshi / Mitra, Chanchal K. / Pauling, Josch K. / Rawlings, Chris / Fdez-Riverola, Florentino / Romano, Paolo / Röttger, Richard / Shoshi, Alban / Soares, Siomar de Castro / Taubert, Jan / Tauch, Andreas / Yousef, Malik / Weise, Stephan

4 Issues per year


CiteScore 2017: 0.77

SCImago Journal Rank (SJR) 2017: 0.336

Open Access
Online
ISSN
1613-4516
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Volume 7, Issue 3

Issues

Enhancing Data Integration with Text Analysis to Find Proteins Implicated in Plant Stress Response

Keywan Hassani-Pak
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  • Centre for Mathematical and Computational Biology, Rothamsted Research, United Kingdom of Great Britain and Northern Ireland
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/ Roxane Legaie
  • Warwick Systems Biology Centre, University of Warwick, United Kingdom of Great Britain and Northern Ireland
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/ Catherine Canevet
  • Centre for Mathematical and Computational Biology, Rothamsted Research, United Kingdom of Great Britain and Northern Ireland
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/ Hugo A. van den Berg
  • Warwick Systems Biology Centre, University of Warwick, United Kingdom of Great Britain and Northern Ireland
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/ Jonathan D. Moore
  • Warwick Systems Biology Centre, University of Warwick, United Kingdom of Great Britain and Northern Ireland
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/ Christopher J. Rawlings
  • Centre for Mathematical and Computational Biology, Rothamsted Research, United Kingdom of Great Britain and Northern Ireland
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Published Online: 2016-10-18 | DOI: https://doi.org/10.1515/jib-2010-121

Summary

High throughput genomic studies can identify large numbers of potential candidate genes, which must be interpreted and filtered by investigators to select the best ones for further analysis. Prioritization is generally based on evidence that supports the role of a gene product in the biological process being investigated. The two most important bodies of information providing such evidence are bioinformatics databases and the scientific literature. In this paper we present an extension to the Ondex data integration framework that uses text mining techniques over Medline abstracts as a method for accessing both these bodies of evidence in a consistent way. In an example use case, we apply our method to create a knowledge base of Arabidopsis proteins implicated in plant stress response and use various scoring metrics to identify key protein-stress associations. In conclusion, we show that the additional text mining features are able to highlight proteins using the scientific literature that would not have been seen using data integration alone. Ondex is an open-source software project and can be downloaded, together with the text mining features described here, from www.ondex.org.

About the article

Published Online: 2016-10-18

Published in Print: 2010-12-01


Citation Information: Journal of Integrative Bioinformatics, Volume 7, Issue 3, Pages 87–99, ISSN (Online) 1613-4516, DOI: https://doi.org/10.1515/jib-2010-121.

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© 2010 The Author(s). Published by Journal of Integrative Bioinformatics.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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