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Philippe Charton

Showing results (1-10 of 7) with videos related to

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Protein Engineering, Design & Selection : PEDS|August 30, 2014
A web-based tool for rational screening of mutants libraries using ProSARMagali Berland, Bernard Offmann, Isabelle André, et al.
Plos One|June 12, 2026
Unimodal vs. multimodal deep learning for non-invasive MGMT promoter methylation prediction in glioblastoma: A systematic evaluation on the BraTS 2021 datasetFreddy Oulia, Philippe Charton, Muhammad Kabir, et al.
BMC Bioinformatics|October 18, 2018
Application of fourier transform and proteochemometrics principles to protein engineeringFrédéric Cadet, Nicolas Fontaine, Iyanar Vetrivel, et al.
Scientific Reports|August 12, 2020
Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approachesOphélie Lo-Thong, Philippe Charton, Xavier F Cadet, et al.
Frontiers in Artificial Intelligence|June 27, 2022
Non-linearity of Metabolic Pathways Critically Influences the Choice of Machine Learning ModelOphélie Lo-Thong-Viramoutou, Philippe Charton, Xavier F Cadet, et al.
Plos One|May 9, 2019
Flux prediction using artificial neural network (ANN) for the upper part of glycolysisAnamya Ajjolli Nagaraja, Nicolas Fontaine, Mathieu Delsaut, et al.
International Journal of Molecular Sciences|January 8, 2025
Metabolic Fluxes Using Deep Learning Based on Enzyme Variations: <i>Application to Glycolysis in Entamoeba histolytica</i>Freddy Oulia, Philippe Charton, Ophélie Lo-Thong-Viramoutou, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Protein Engineering, Design & Selection : PEDS|August 30, 2014
A web-based tool for rational screening of mutants libraries using ProSARMagali Berland, Bernard Offmann, Isabelle André, et al.
Plos One|June 12, 2026
Unimodal vs. multimodal deep learning for non-invasive MGMT promoter methylation prediction in glioblastoma: A systematic evaluation on the BraTS 2021 datasetFreddy Oulia, Philippe Charton, Muhammad Kabir, et al.
BMC Bioinformatics|October 18, 2018
Application of fourier transform and proteochemometrics principles to protein engineeringFrédéric Cadet, Nicolas Fontaine, Iyanar Vetrivel, et al.
Scientific Reports|August 12, 2020
Identification of flux checkpoints in a metabolic pathway through white-box, grey-box and black-box modeling approachesOphélie Lo-Thong, Philippe Charton, Xavier F Cadet, et al.
Frontiers in Artificial Intelligence|June 27, 2022
Non-linearity of Metabolic Pathways Critically Influences the Choice of Machine Learning ModelOphélie Lo-Thong-Viramoutou, Philippe Charton, Xavier F Cadet, et al.
Plos One|May 9, 2019
Flux prediction using artificial neural network (ANN) for the upper part of glycolysisAnamya Ajjolli Nagaraja, Nicolas Fontaine, Mathieu Delsaut, et al.
International Journal of Molecular Sciences|January 8, 2025
Metabolic Fluxes Using Deep Learning Based on Enzyme Variations: <i>Application to Glycolysis in Entamoeba histolytica</i>Freddy Oulia, Philippe Charton, Ophélie Lo-Thong-Viramoutou, et al.
Pageof 1