A4 Refereed article in a conference publication
Integrating Large-Scale Text Mining and Co-Expression Networks: Targeting NADP(H) Metabolism in E. coli with Event Extraction
Authors: Suwisa Kaewphan, Sanna Kreula, Sofie Van Landeghem, Yves Van de Peer, Patrik R Jones, Filip Ginter
Editors: ECCB'12 Steering Committee
Conference name: Third Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM 2012)
Publication year: 2012
Book title : Third Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM 2012)
First page : 8
Last page: 15
Number of pages: 8
eISBN: 978-2-9517408-7-7
Web address : http://www.lrec-conf.org/proceedings/lrec2012/index.html(external)
We present an application of EVEX, a literature-scale event extraction resource, in the concrete biological use case of NADP(H)
metabolism regulation in Escherichia coli. We make extensive use of the EVEX event generalization based on gene family definitions
in Ensembl Genomes, to extract cross-species candidate regulators. We manually evaluate the resulting network so as to only preserve
correct events and facilitate its integration with microarray-based co-expression data. When analysing the combined network obtained
from text mining and co-expression, we identify 41 candidate genes involved in triangular patterns involving both subnetworks. Several
of these candidates are of particular interest, and we discuss their biological relevance further. This study is the first to present a
real-world evaluation of the EVEX resource in particular and literature-scale application of the systems emerging from the BioNLP
Shared Task series in general. We summarize the lessons learned from this use case in order to focus future development of EVEX and
similar literature-scale resources.
Downloadable publication This is an electronic reprint of the original article. |  |
