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  Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks

Prigent, S., Frioux, C., Dittami, S. M., Thiele, S., Larhlimi, A., Collet, G., et al. (2017). Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks. PLoS Computational Biology, 13: e1005276. doi: 10.1371/journal.pcbi.1005276.

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© 2017 Prigent et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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 Creators:
Prigent, S.1, Author
Frioux, C.1, Author
Dittami, S. M.2, Author
Thiele, Sven3, Author           
Larhlimi, A.4, Author
Collet, G.1, Author
Gutknecht, F.5, Author
Got, J.1, Author
Eveillard, D.4, Author
Bourdon, J.4, Author
Plewniak, F.5, Author
Tonon, T.6, Author
Siegel, A.1, Author
Affiliations:
1Institute for Research in IT and Random Systems - IRISA, Université de Rennes 1, Rennes, France, Department of Biology and Biological Engineering, Chalmers University of Technology, Göteborg, Sweden, Irisa, CNRS, Rennes, France, Dyliss, Inria, Rennes, France , ou_persistent22              
2Sorbonne Universités, UPMC Univ Paris 06, CNRS, UMR 8227, Integrative Biology of Marine Models, Station Biologique de Roscoff, Roscoff, France , ou_persistent22              
3Analysis and Redesign of Biological Networks, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738139              
4Computer Science Laboratory of Nantes Atlantique - LINA UMR6241, Université de Nantes, Nantes, France , ou_persistent22              
5Molecular Genetics, Genomics and Microbiology - GMGM, Université de Strasbourg, Strasbourg, France , ou_persistent22              
6Centre for Novel Agricultural Products, Department of Biology, University of York, York, UK , ou_persistent22              

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Language(s): eng - English
 Dates: 2017
 Publication Status: Issued
 Pages: -
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 Rev. Type: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1005276
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Title: PLoS Computational Biology
Source Genre: Journal
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Pages: - Volume / Issue: 13 Sequence Number: e1005276 Start / End Page: - Identifier: ISSN: 1553-734X