Publications

Flux prediction using artificial neural network (ANN) for the upper part of glycolysis

A machine learning approach for reliable prediction of amino acid interactions and its application in the directed evolution of enantioselective enzymes

Application of fourier transform and proteochemometrics principles to protein engineering

Published: October 16, 2018

Authors: Frédéric Cadet, Nicolas FontaineIyanar VetrivelMatthieu Ng Fuk ChongOlivier SavriamaXavier Cadet, Philippe Charton

Journal: BMC Bioinformatics

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Modeling of a Cell-Free Synthetic System for Biohydrogen Production

Published: March 30, 2015

Authors: Nicolas Fontaine, Brigitte Grondin-Perez, Frederic Cadet, Bernard Offmann 

Journal: Journal of Computer Science & Systems Biology

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Use of a structural alphabet to find compatible folds for amino acid sequences

Analysis of loop boundaries using different local structure assignment methods

Protein short loop prediction in terms of a structural alphabet

Published: June 25, 2009

Authors: Manoj Tyagi, Aurélie Bornot, Bernard Offmann, Alexandre G. de Brevern

Journal: Computational Biology and Chemistry

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PEACCEL’s founders publications

Converting bulk sugars into prebiotics: semi-rational design of a transglucosylase with controlled selectivity

DoSA: Database of Structural Alignments

Correlation between local structural dynamics of proteins inferred from NMR ensembles and evolutionary dynamics of homologues of known structure

Published: June 3, 2013

Authors: Swapnil Mahajan, Alexandre G. de Brevern, Bernard Offmann, Narayanaswamy Srinivasan

Journal: Journal of Biomolecular Structure and Dynamics

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A substitution matrix for structural alphabet based on structural alignment of homologous proteins and its applications

Published: August 7, 2006

Authors: Manoj Tyagi, Venkataraman S. Gowri, Narayanaswamy Srinivasan, Alexandre G. de Brevern, Bernard Offmann

Journal: Proteins: Structure, Function, and Bioinformatics

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Native and modeled disulfide bonds in proteins: Knowledge-based approaches toward structure prediction of disulfide-rich polypeptides