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          Institute: MPI für molekulare Genetik     Collection: Department of Vertebrate Genomics     Display Documents



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ID: 456813.0, MPI für molekulare Genetik / Department of Vertebrate Genomics
Reverse Engineering of Gene Regulatory Networks: A Comparative Study.
Authors:Hache, Hendrik; Lehrach, Hans; Herwig, Ralf
Language:English
Date of Publication (YYYY-MM-DD):2009-03-11
Title of Journal:EURASIP Journal on Bioinformatics and Systems Biology
Journal Abbrev.:EURASIP JBSB
Volume:2009
Sequence Number of Article:ID 617281
Full name of Issue-Editor(s):Repsilber, Dirk
Copyright:2009 Hendrik Hache et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Review Status:not specified
Audience:Experts Only
Abstract / Description:Reverse engineering of gene regulatory networks has been an intensively studied topic in bioinformatics since it constitutes an intermediate step from explorative to causative gene expression analysis. Many methods have been proposed through recent years leading to a wide range of mathematical approaches. In practice, different mathematical approaches will generate different resulting network structures, thus, it is very important for users to assess the performance of these algorithms. We have conducted a comparative study with six different reverse engineering methods, including relevance networks, neural networks, and Bayesian networks. Our approach consists of the generation of defined benchmark data, the analysis of these data with the different methods, and the assessment of algorithmic performances by statistical analyses. Performance was judged by network size and noise levels. The results of the comparative study highlight the neural network approach as best performing method among those under study.
External Publication Status:published
Document Type:Article
Communicated by:Hans Lehrach
Affiliations:MPI für molekulare Genetik
Identifiers:URL:http://www.hindawi.com/journals/bsb/2009/617281.ht...
DOI:10.1155/2009/617281
ISSN:1687-4145
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