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Panuwat Trairatphisan

Showing results (1-10 of 20) with videos related to

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Bioinformatics (Oxford, England)|July 5, 2017
FALCON: a toolbox for the fast contextualization of logical networksSébastien De Landtsheer, Panuwat Trairatphisan, Philippe Lucarelli, et al.
Plos One|May 28, 2016
A Probabilistic Boolean Network Approach for the Analysis of Cancer-Specific Signalling: A Case Study of Deregulated PDGF Signalling in GISTPanuwat Trairatphisan, Monique Wiesinger, Christelle Bahlawane, et al.
Plos One|July 2, 2014
optPBN: an optimisation toolbox for probabilistic Boolean networksPanuwat Trairatphisan, Andrzej Mizera, Jun Pang, et al.
NPJ Systems Biology and Applications|November 16, 2019
From expression footprints to causal pathways: contextualizing large signaling networks with CARNIVALAnika Liu, Panuwat Trairatphisan, Enio Gjerga, et al.
Cell Communication and Signaling : CCS|July 3, 2013
Recent development and biomedical applications of probabilistic Boolean networksPanuwat Trairatphisan, Andrzej Mizera, Jun Pang, et al.
Toxicology Letters|July 6, 2021
Contextualization of causal regulatory networks from toxicogenomics data applied to drug-induced liver injuryPanuwat Trairatphisan, Terezinha Maria de Souza, Jos Kleinjans, et al.
Frontiers in Genetics|December 6, 2018
Embracing the Dark Side: Computational Approaches to Unveil the Functionality of Genes Lacking Biological Annotation in Drug-Induced Liver InjuryTerezinha Souza, Panuwat Trairatphisan, Janet Piñero, et al.
Environmental and Molecular Mutagenesis|December 31, 2024
Machine learning enhances genotoxicity assessment using MultiFlow® DNA damage assayPanuwat Trairatphisan, Lena Dorsheimer, Peter Monecke, et al.
Bioinformatics (Oxford, England)|June 10, 2020
Converting networks to predictive logic models from perturbation signalling data with CellNOptEnio Gjerga, Panuwat Trairatphisan, Attila Gabor, et al.
Journal of Chemical Information and Modeling|November 18, 2025
A Simple Framework for Collaborative Development of Predictive Models Trained on Proprietary DataPablo Rodríguez-Belenguer, Alexander Amberg, Frank Bringezu, et al.
Pageof 2

Showing results (1-10 of 20) with videos related to

Sort By:
Pageof 2
Bioinformatics (Oxford, England)|July 5, 2017
FALCON: a toolbox for the fast contextualization of logical networksSébastien De Landtsheer, Panuwat Trairatphisan, Philippe Lucarelli, et al.
Plos One|May 28, 2016
A Probabilistic Boolean Network Approach for the Analysis of Cancer-Specific Signalling: A Case Study of Deregulated PDGF Signalling in GISTPanuwat Trairatphisan, Monique Wiesinger, Christelle Bahlawane, et al.
Plos One|July 2, 2014
optPBN: an optimisation toolbox for probabilistic Boolean networksPanuwat Trairatphisan, Andrzej Mizera, Jun Pang, et al.
NPJ Systems Biology and Applications|November 16, 2019
From expression footprints to causal pathways: contextualizing large signaling networks with CARNIVALAnika Liu, Panuwat Trairatphisan, Enio Gjerga, et al.
Cell Communication and Signaling : CCS|July 3, 2013
Recent development and biomedical applications of probabilistic Boolean networksPanuwat Trairatphisan, Andrzej Mizera, Jun Pang, et al.
Toxicology Letters|July 6, 2021
Contextualization of causal regulatory networks from toxicogenomics data applied to drug-induced liver injuryPanuwat Trairatphisan, Terezinha Maria de Souza, Jos Kleinjans, et al.
Frontiers in Genetics|December 6, 2018
Embracing the Dark Side: Computational Approaches to Unveil the Functionality of Genes Lacking Biological Annotation in Drug-Induced Liver InjuryTerezinha Souza, Panuwat Trairatphisan, Janet Piñero, et al.
Environmental and Molecular Mutagenesis|December 31, 2024
Machine learning enhances genotoxicity assessment using MultiFlow® DNA damage assayPanuwat Trairatphisan, Lena Dorsheimer, Peter Monecke, et al.
Bioinformatics (Oxford, England)|June 10, 2020
Converting networks to predictive logic models from perturbation signalling data with CellNOptEnio Gjerga, Panuwat Trairatphisan, Attila Gabor, et al.
Journal of Chemical Information and Modeling|November 18, 2025
A Simple Framework for Collaborative Development of Predictive Models Trained on Proprietary DataPablo Rodríguez-Belenguer, Alexander Amberg, Frank Bringezu, et al.
Pageof 2