World's Best Scientists 2026 revealed!
Giorgio Valentini

Giorgio Valentini

D-Index & Metrics

Computer Science

D-Index
39
Citations
6110
World Ranking
9795
National Ranking
292

Overview

Giorgio Valentini is affiliated with the University of Milan in Italy. Their work spans several fields, primarily focusing on Biochemistry, Genetics and Molecular Biology, Medicine, and Computer Science. Within these broader fields, their research has concentrated on subfields such as Molecular Biology, Artificial Intelligence, Genetics, Infectious Diseases, and Neurology.

Their research topics include:

  • Bioinformatics and Genomic Networks
  • Biomedical Text Mining and Ontologies
  • RNA and protein synthesis mechanisms
  • Machine Learning in Bioinformatics
  • Gene expression and cancer classification
  • COVID-19 Clinical Research Studies
  • Advanced Graph Neural Networks

Valentini has published extensively, with frequent appearances in venues including:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • PLoS ONE
  • Bioinformatics
  • Bioinformatics Advances

Recent notable publications include:

  • "Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes," 2022, EBioMedicine
  • "Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments," 2020, IEEE Access
  • "Interpretable prioritization of splice variants in diagnostic next-generation sequencing," 2021, The American Journal of Human Genetics
  • "An open source knowledge graph ecosystem for the life sciences," 2024, Scientific Data
  • "On the limitations of large language models in clinical diagnosis," 2023, bioRxiv (Cold Spring Harbor Laboratory)

Frequent collaborators include Elena Casiraghi, Peter N. Robinson, Justin Reese, Luca Cappelletti, and Chris Mungall. These collaborations reflect a cross-disciplinary approach involving computational biology and clinical research.

Best Publications

  • Ensembles of Learning Machines

    Giorgio Valentini;Francesco Masulli

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

  • The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

    Naihui Zhou;Yuxiang Jiang;Timothy R. Bergquist;Alexandra J. Lee

  • Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods

    Giorgio Valentini;Thomas G. Dietterich

  • A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease

    Damian Smedley;Max Schubach;Julius O O.B. Jacobsen;Sebastian Köhler

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T Clark;Asma R Bankapur

  • True Path Rule Hierarchical Ensembles for Genome-Wide Gene Function Prediction

    Giorgio Valentini

  • Cancer recognition with bagged ensembles of support vector machines

    Giorgio Valentini;Marco Muselli;Francesca Ruffino

  • Fuzzy ensemble clustering based on random projections for DNA microarray data analysis

    Roberto Avogadri;Giorgio Valentini

  • Imbalance-Aware Machine Learning for Predicting Rare and Common Disease-Associated Non-Coding Variants.

    Max Schubach;Matteo Re;Peter N. Robinson;Peter N. Robinson;Giorgio Valentini

  • Low bias bagged support vector machines

    Giorgio Valentini;Thomas G. Dietterich

  • Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference

    Nicolò Cesa-Bianchi;Matteo Re;Giorgio Valentini

  • Ensemble methods : a review

    M. Re;G. Valentini

  • Letters: Bio-molecular cancer prediction with random subspace ensembles of support vector machines

    Alberto Bertoni;Raffaella Folgieri;Giorgio Valentini

  • An experimental bias-variance analysis of SVM ensembles based on resampling techniques

    G. Valentini

  • Interpretable prioritization of splice variants in diagnostic next-generation sequencing.

    Daniel Danis;Julius O.B. Jacobsen;Leigh C. Carmody;Michael A. Gargano

  • Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments

    Elena Casiraghi;Dario Malchiodi;Gabriella Trucco;Marco Frasca

  • The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

    Naihui Zhou;Yuxiang Jiang;Timothy R Bergquist;Alexandra J Lee

  • An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods

    Giorgio Valentini;Alberto Paccanaro;Horacio Caniza;Alfonso E. Romero

  • Letters: Support vector machines for candidate nodules classification

    Paola Campadelli;Elena Casiraghi;Giorgio Valentini

  • GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology

    Horacio Caniza;Alfonso E. Romero;Samuel Heron;Haixuan Yang

  • Gene expression data analysis of human lymphoma using support vector machines and output coding ensembles

    Giorgio Valentini

  • Applications of Supervised and Unsupervised Ensemble Methods

    Oleg Okun;Giorgio Valentini

  • Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

Frequent Co-Authors

Peter N. Robinson
Peter N. Robinson The Jackson Laboratory
Christophe Dessimoz
Christophe Dessimoz University College London
David T. Jones
David T. Jones University College London
Tapio Salakoski
Tapio Salakoski University of Turku
Daisuke Kihara
Daisuke Kihara Purdue University West Lafayette
Burkhard Rost
Burkhard Rost Technical University of Munich
Steven E. Brenner
Steven E. Brenner University of California, Berkeley
Julian Gough
Julian Gough University of Bristol
Michal Linial
Michal Linial Hebrew University of Jerusalem
Predrag Radivojac
Predrag Radivojac Northeastern University

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