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SAR and QSAR in Environmental Research|July 6, 2000
Neural networks predict protein folding and structure: artificial intelligence faces biomolecular complexityR Casadio, M Compiani, P Fariselli, et al.
Proceedings of the National Academy of Sciences of the United States of America|August 5, 1998
An entropy criterion to detect minimally frustrated intermediates in native proteinsM Compiani, P Fariselli, P L Martelli, et al.
Proceedings. International Conference on Intelligent Systems for Molecular Biology|April 29, 2000
A data base of minimally frustrated alpha helical segments extracted from proteins according to an entropy criterionR Casadio, M Compiani, P Fariselli, et al.
Protein Science : a Publication of the Protein Society|March 29, 2001
Prediction of the transmembrane regions of beta-barrel membrane proteins with a neural network-based predictorI Jacoboni, P L Martelli, P Fariselli, et al.
SAR and QSAR in Environmental Research|August 20, 2002
Protein structure prediction and biomolecular recognition: from protein sequence to peptidomimetic design with the human beta3 integrinR Casadio, M Compiani, A Facchiano, et al.
European Biophysics Journal : EBJ|January 1, 1993
Predicting secondary structures of membrane proteins with neural networksP Fariselli, M Compiani, R Casadio
European Biophysics Journal : EBJ|January 1, 1996
A predictor of transmembrane alpha-helix domains of proteins based on neural networksR Casadio, P Fariselli, C Taroni, et al.
Proceedings. International Conference on Intelligent Systems for Molecular Biology|January 1, 1995
Predicting free energy contributions to the conformational stability of folded proteins from the residue sequence with radial basis function networksR Casadio, M Compiani, P Fariselli, et al.
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