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Bioinformatics (Oxford, England)|February 8, 2017
SChloro: directing Viridiplantae proteins to six chloroplastic sub-compartmentsCastrense Savojardo, Pier Luigi Martelli, Piero Fariselli, et al.BMC Bioinformatics|February 2, 2013
Prediction of disulfide connectivity in proteins with machine-learning methods and correlated mutationsCastrense Savojardo, Piero Fariselli, Pier Luigi Martelli, et al.Bioinformatics (Oxford, England)|December 28, 2017
DeepSig: deep learning improves signal peptide detection in proteinsCastrense Savojardo, Pier Luigi Martelli, Piero Fariselli, et al.Briefings in Bioinformatics|December 31, 2019
On the critical review of five machine learning-based algorithms for predicting protein stability changes upon mutationCastrense Savojardo, Pier Luigi Martelli, Rita Casadio, et al.Bioinformatics (Oxford, England)|May 10, 2015
INPS: predicting the impact of non-synonymous variations on protein stability from sequencePiero Fariselli, Pier Luigi Martelli, Castrense Savojardo, et al.Comparative and Functional Genomics|July 17, 2008
The prediction of membrane protein structure and genome structural annotationPier Luigi Martelli, Piero Fariselli, Gianluca Tasco, et al.Bioinformatics (Oxford, England)|June 17, 2015
TPpred3 detects and discriminates mitochondrial and chloroplastic targeting peptides in eukaryotic proteinsCastrense Savojardo, Pier Luigi Martelli, Piero Fariselli, et al.Nucleic Acids Research|November 17, 2006
eSLDB: eukaryotic subcellular localization databaseAndea Pierleoni, Pier Luigi Martelli, Piero Fariselli, et al.Bioinformatics (Oxford, England)|August 10, 2002
A sequence-profile-based HMM for predicting and discriminating beta barrel membrane proteinsPier Luigi Martelli, Piero Fariselli, Anders Krogh, et al.Protein Engineering|February 26, 2003
Prediction of the disulfide bonding state of cysteines in proteins with hidden neural networksPier Luigi Martelli, Piero Fariselli, Luca Malaguti, et al.Pageof 20