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  Detecting and Removing Inconsistencies between Experimental Data and Signaling Network Topologies Using Integer Linear Programming on Interaction Graphs

Melas, I. N., Samaga, R., Alexopoulos, L. G., & Klamt, S. (2013). Detecting and Removing Inconsistencies between Experimental Data and Signaling Network Topologies Using Integer Linear Programming on Interaction Graphs. PLoS Computational Biology, 9(9), e1003204. doi:10.1371/journal.pcbi.1003204.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0014-636F-6 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-002C-904C-1
Genre: Journal Article

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1837078_samaga.pdf (Publisher version), 2MB
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2013 Melas 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:
Melas, Ioannis N.1, Author
Samaga, Regina2, Author           
Alexopoulos, Leonidas G.1, Author
Klamt, Steffen2, Author           
Affiliations:
1National Technical University of Athens, Greece, ou_1738139              
2Analysis and Redesign of Biological Networks, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738139              

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Language(s): eng - English
 Dates: 2013
 Publication Status: Issued
 Pages: -
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 Rev. Type: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1003204
Other: 38/13
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Title: PLoS Computational Biology
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 9 (9) Sequence Number: - Start / End Page: e1003204 Identifier: CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1