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Castrense Savojardo

Showing results (1-10 of 89) with videos related to

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Bioinformatics (Oxford, England)|October 5, 2011
Improving the detection of transmembrane β-barrel chains with N-to-1 extreme learning machinesCastrense Savojardo, Piero Fariselli, Rita Casadio
Bioinformatics (Oxford, England)|January 9, 2013
BETAWARE: a machine-learning tool to detect and predict transmembrane beta-barrel proteins in prokaryotesCastrense Savojardo, Piero Fariselli, Rita Casadio
International Journal of Molecular Sciences|June 24, 2022
Molecular Effects of Mutations in Human Genetic DiseasesEmanuela Leonardi, Castrense Savojardo, Giovanni Minervini
Current Opinion in Structural Biology|June 29, 2023
Finding functional motifs in protein sequences with deep learning and natural language modelsCastrense Savojardo, Pier Luigi Martelli, Rita Casadio
Bioinformatics (Oxford, England)|May 7, 2016
INPS-MD: a web server to predict stability of protein variants from sequence and structureCastrense Savojardo, Piero Fariselli, Pier Luigi Martelli, et al.
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.
Pageof 9

Showing results (1-10 of 89) with videos related to

Sort By:
Pageof 9
Bioinformatics (Oxford, England)|October 5, 2011
Improving the detection of transmembrane β-barrel chains with N-to-1 extreme learning machinesCastrense Savojardo, Piero Fariselli, Rita Casadio
Bioinformatics (Oxford, England)|January 9, 2013
BETAWARE: a machine-learning tool to detect and predict transmembrane beta-barrel proteins in prokaryotesCastrense Savojardo, Piero Fariselli, Rita Casadio
International Journal of Molecular Sciences|June 24, 2022
Molecular Effects of Mutations in Human Genetic DiseasesEmanuela Leonardi, Castrense Savojardo, Giovanni Minervini
Current Opinion in Structural Biology|June 29, 2023
Finding functional motifs in protein sequences with deep learning and natural language modelsCastrense Savojardo, Pier Luigi Martelli, Rita Casadio
Bioinformatics (Oxford, England)|May 7, 2016
INPS-MD: a web server to predict stability of protein variants from sequence and structureCastrense Savojardo, Piero Fariselli, Pier Luigi Martelli, et al.
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.
Pageof 9