Piero Fariselli regularly ties together related areas like Protein function in his Gene studies. Piero Fariselli conducted interdisciplinary study in his works that combined Computational biology and ENCODE. In his works, Piero Fariselli undertakes multidisciplinary study on ENCODE and Computational biology. He performs multidisciplinary study in the fields of Genetics and Mutation via his papers. As part of his studies on Artificial intelligence, Piero Fariselli often connects relevant areas like Hidden Markov model. In his articles, he combines various disciplines, including Biochemistry and Protein folding. In his papers, he integrates diverse fields, such as Machine learning and Statistics. In his articles, Piero Fariselli combines various disciplines, including Statistics and Machine learning. With his scientific publications, his incorporates both Data mining and Algorithm.
Piero Fariselli bridges between several scientific fields such as Pattern recognition (psychology) and Artificial neural network in his study of Artificial intelligence. Piero Fariselli conducts interdisciplinary study in the fields of Gene and Mutation through his research. He combines Computational biology and Bioinformatics in his research. His work blends Bioinformatics and Computational biology studies together. His research on Biochemistry often connects related topics like Sequence (biology). His research ties Biochemistry and Sequence (biology) together. He merges many fields, such as Genetics and Genome, in his writings. With his scientific publications, his incorporates both Genome and Genetics. In his works, Piero Fariselli performs multidisciplinary study on Machine learning and Stability (learning theory).
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I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure.
Emidio Capriotti;Piero Fariselli;Rita Casadio.
Nucleic Acids Research (2005)
Topology prediction for helical transmembrane proteins at 86% accuracy.
Burkhard Rost;Piero Fariselli;Rita Casadio.
Protein Science (1996)
Transmembrane helices predicted at 95% accuracy
Burkhard Rost;Rita Casadio;Piero Fariselli;Chris Sander.
Protein Science (2008)
Functional annotations improve the predictive score of human disease-related mutations in proteins
Remo Calabrese;Emidio Capriotti;Piero Fariselli;Pier Luigi Martelli.
Human Mutation (2009)
ConSeq: the identification of functionally and structurally important residues in protein sequences
Carine Berezin;Fabian Glaser;Josef Rosenberg;Inbal Paz.
BaCelLo: a Balanced subCellular Localization predictor
Andrea Pierleoni;Pier Luigi Martelli;Piero Fariselli;Rita Casadio.
Prediction of protein--protein interaction sites in heterocomplexes with neural networks.
Piero Fariselli;Florencio Pazos;Alfonso Valencia;Rita Casadio.
FEBS Journal (2002)
A three-state prediction of single point mutations on protein stability changes
Emidio Capriotti;Piero Fariselli;Ivan Rossi;Rita Casadio.
BMC Bioinformatics (2008)
Prediction of contact maps with neural networks and correlated mutations
Piero Fariselli;Osvaldo Olmea;Alfonso Valencia;Rita Casadio.
Protein Engineering (2001)
The implications of alternative splicing in the ENCODE protein complement
Michael L. Tress;Pier Luigi Martelli;Adam Frankish;Gabrielle A. Reeves.
Proceedings of the National Academy of Sciences of the United States of America (2007)
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