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  Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling

D`Allessandro, L. A., Samaga, R., Maiwald, T., Rho, S.-H., Bonefas, S., Raue, A., et al. (2015). Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling. PLoS Computational Biology, 11(4): e1004192. doi: 10.1371/journal.pcbi.1004192.

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Copyright: © 2015 D’Alessandro et al. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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 Creators:
D`Allessandro, Lorenza A.1, Author
Samaga, Regina2, Author           
Maiwald, Tim3, Author
Rho, Seong-Hwan4, Author
Bonefas, Sandra1, Author
Raue, Andreas3, Author
Iwamoto, Nao1, Author
Kienast, Alexandra1, Author
Waldow, Katharina1, Author
Meyer, Rene1, Author
Schilling, Marcel1, Author
Timmer, Jens3, Author
Klamt, Steffen2, Author           
Klingmüller, Ursula1, Author
Affiliations:
1Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), INF 280, Heidelberg, Germany , ou_persistent22              
2Analysis and Redesign of Biological Networks, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738139              
3 Institute of Physics, University of Freiburg, Freiburg, Germany, BIOSS Centre for Biological Signalling Studies, University of Freiburg, Freiburg, Germany , ou_persistent22              
4Simulacre Modeling Group, 953–1 Madu1-dong, Goyang, Korea , ou_persistent22              

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 Dates: 2015
 Publication Status: Issued
 Pages: -
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 Rev. Type: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1004192
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Project name : CANCERSYS - "Mathematical modelling of beta-catenin and ras signalling in liver and its impact on proliferation, tissue organization and formation of hepatocellular carcinomas"
Grant ID : 223188
Funding program : Funding Programme 7 (FP7)
Funding organization : European Commission (EC)

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Title: PLoS Computational Biology
Source Genre: Journal
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Pages: - Volume / Issue: 11 (4) Sequence Number: e1004192 Start / End Page: - Identifier: ISSN: 1553-734X