Bernard Offmann

Affiliations: 
2002-2011 LBGM Universite de La Reunion, France 
 2011- UFIP UMR CNRS 6286 Université de Nantes 
Area:
Protein structures, Pentapeptides, Mosquito, Hydrogen production, Fkbp12, Molecular recognition, High-Affinity ligand, Proteins, Protein engineering, Machine learning
Website:
http://www.bernardoffmann.fr
Google:
"Bernard Offmann"
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Publications

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Gheyouche E, Bagueneau M, Loirand G, et al. (2021) Structural Design and Analysis of the RHOA-ARHGEF1 Binding Mode: Challenges and Applications for Protein-Protein Interface Prediction. Frontiers in Molecular Biosciences. 8: 643728
Cadet F, Fontaine N, Li G, et al. (2021) Publisher Correction: A machine learning approach for reliable prediction of amino acid interactions and its application in the directed evolution of enantioselective enzymes. Scientific Reports. 11: 8357
Dhingra S, Sowdhamini R, Cadet F, et al. (2020) A glance into the evolution of template-free protein structure prediction methodologies. Biochimie
Liu G, Xuan N, Rajashekar B, et al. (2020) Comprehensive History of Genes: Evolution, Phylogenetic Distribution and Functions. Genes. 11
Nagaraja AA, Charton P, Cadet XF, et al. (2020) A Machine Learning Approach for Efficient Selection of Enzyme Concentrations and Its Application for Flux Optimization Catalysts. 10: 291
Vetrivel I, de Brevern AG, Cadet F, et al. (2019) Structural variations within proteins can be as large as variations observed across their homologues. Biochimie
Ostafe R, Fontaine N, Frank D, et al. (2019) One-shot Optimization of Multiple Enzyme Parameters: Tailoring Glucose Oxidase for pH and Electron Mediators. Biotechnology and Bioengineering
Ghosh P, Joshi A, Guita N, et al. (2019) EcRBPome: a comprehensive database of all known E. coli RNA-binding proteins. Bmc Genomics. 20: 403
Ajjolli Nagaraja A, Fontaine N, Delsaut M, et al. (2019) Flux prediction using artificial neural network (ANN) for the upper part of glycolysis. Plos One. 14: e0216178
Cadet F, Fontaine N, Li G, et al. (2018) A machine learning approach for reliable prediction of amino acid interactions and its application in the directed evolution of enantioselective enzymes. Scientific Reports. 8: 16757
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