World's Best Scientists 2026 revealed!
Piero Fariselli

Piero Fariselli

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Computer Science
Italy
2025

D-Index & Metrics

Computer Science

D-Index
53
Citations
14598
World Ranking
4734
National Ranking
100

Research.com Recognitions

  • 2025 - Research.com Computer Science in Italy Leader Award
  • 2022 - Research.com Computer Science in Italy Leader Award

Overview

Piero Fariselli is affiliated with the University of Turin in Italy and has contributed extensively to research within biochemistry, genetics, and molecular biology as well as medicine. Their work spans a range of topics related to molecular and genomic sciences, with a specific focus on protein dynamics, genomics, and disease diagnosis.

The following recent papers illustrate the scope and focus of their research:

  • DOME: recommendations for supervised machine learning validation in biology, 2021, Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano)
  • Caucasian lean subjects with non-alcoholic fatty liver disease share long-term prognosis of non-lean: time for reappraisal of BMI-driven approach?, 2021, Gut
  • Long-term outcomes and predictive ability of non-invasive scoring systems in patients with non-alcoholic fatty liver disease, 2021, Journal of Hepatology
  • Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine, 2020, Computational and Structural Biotechnology Journal
  • Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset, 2021, Briefings in Bioinformatics

Piero Fariselli frequently collaborates with a core group of co-authors, including:

  • Tiziana Sanavia
  • Giovanni Birolo
  • Cesare Rollo
  • Emidio Capriotti
  • Corrado Pancotti

Their publications are disseminated in various scientific venues, with several appearing multiple times in certain journals and repositories:

  • Blood
  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Frontiers in Molecular Biosciences

The main fields of study for Piero Fariselli include biochemistry, genetics, molecular biology, and medicine. They have a significant body of work in molecular biology and genetics, with additional interests in artificial intelligence, cancer research, and epidemiology. These fields support a research agenda oriented toward understanding biological mechanisms and clinical applications.

The subfields and topics of interest that characterize their work include:

  • Molecular Biology
  • Genetics
  • Artificial Intelligence
  • Cancer Research
  • Epidemiology

  • RNA and protein synthesis mechanisms
  • Genomics and Phylogenetic Studies
  • Protein Structure and Dynamics
  • Genomics and Rare Diseases
  • Cancer Genomics and Diagnostics
  • Bioinformatics and Genomic Networks
  • Liver Disease Diagnosis and Treatment

Best Publications

  • I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure.

    Emidio Capriotti;Piero Fariselli;Rita Casadio

  • Topology prediction for helical transmembrane proteins at 86% accuracy.

    Burkhard Rost;Piero Fariselli;Rita Casadio

  • Functional annotations improve the predictive score of human disease-related mutations in proteins

    Remo Calabrese;Emidio Capriotti;Piero Fariselli;Pier Luigi Martelli

  • Transmembrane helices predicted at 95% accuracy

    Burkhard Rost;Rita Casadio;Piero Fariselli;Chris Sander

  • ConSeq: the identification of functionally and structurally important residues in protein sequences

    Carine Berezin;Fabian Glaser;Josef Rosenberg;Inbal Paz

  • BUSCA: an integrative web server to predict subcellular localization of proteins.

    Castrense Savojardo;Pier Luigi Martelli;Piero Fariselli;Giuseppe Profiti;Giuseppe Profiti

  • BaCelLo: a Balanced subCellular Localization predictor.

    Andrea Pierleoni;Pier Luigi Martelli;Piero Fariselli;Rita Casadio

  • WS-SNPs&GO: a web server for predicting the deleterious effect of human protein variants using functional annotation

    Emidio Capriotti;Remo Calabrese;Piero Fariselli;Pier Luigi Martelli

  • Prediction of protein--protein interaction sites in heterocomplexes with neural networks.

    Piero Fariselli;Florencio Pazos;Alfonso Valencia;Rita Casadio

  • A three-state prediction of single point mutations on protein stability changes

    Emidio Capriotti;Piero Fariselli;Ivan Rossi;Rita Casadio

  • Prediction of contact maps with neural networks and correlated mutations

    Piero Fariselli;Osvaldo Olmea;Alfonso Valencia;Rita Casadio

  • INPS-MD: a web server to predict stability of protein variants from sequence and structure

    Castrense Savojardo;Piero Fariselli;Pier Luigi Martelli;Rita Casadio

  • A sequence-profile-based HMM for predicting and discriminating beta barrel membrane proteins.

    Pier Luigi Martelli;Piero Fariselli;Anders Krogh;Rita Casadio

  • PhD-SNPg: a webserver and lightweight tool for scoring single nucleotide variants

    Emidio Capriotti;Piero Fariselli

  • A neural-network-based method for predicting protein stability changes upon single point mutations

    Emidio Capriotti;Piero Fariselli;Rita Casadio

  • Predicting protein stability changes from sequences using support vector machines

    Emidio Capriotti;Piero Fariselli;Remo Calabrese;Rita Casadio

  • A neural network based predictor of residue contacts in proteins.

    P. Fariselli;R. Casadio

  • Progress and challenges in predicting protein–protein interaction sites

    Iakes Ezkurdia;Lisa Bartoli;Piero Fariselli;Rita Casadio

  • Role of evolutionary information in predicting the disulfide‐bonding state of cysteine in proteins

    Piero Fariselli;Paola Riccobelli;Rita Casadio

  • DDGun: an untrained method for the prediction of protein stability changes upon single and multiple point variations

    Ludovica Montanucci;Emidio Capriotti;Yotam Frank;Nir Ben-Tal

  • Prediction of the transmembrane regions of β-barrel membrane proteins with a neural network-based predictor

    Irene Jacoboni;Pier Luigi Martelli;Piero Fariselli;Vito De Pinto

  • Predicting protein stability changes from sequence with Support Vector Machines

    Emidio Capriotti;Piero Fariselli;Remo Calabrese;Rita Casadio

Frequent Co-Authors

Rita Casadio
Rita Casadio University of Bologna
Anders Krogh
Anders Krogh University of Copenhagen
Nir Ben-Tal
Nir Ben-Tal Tel Aviv University
David T. Jones
David T. Jones University College London
Burkhard Rost
Burkhard Rost Technical University of Munich
Yves Moreau
Yves Moreau KU Leuven
Luca Bargelloni
Luca Bargelloni University of Padua
Tomaso Patarnello
Tomaso Patarnello University of Padua
Giuseppe Matullo
Giuseppe Matullo University of Turin
Stylianos E. Antonarakis
Stylianos E. Antonarakis University of Geneva

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