Giorgio Valentini

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Peter RobinsonBerlin Institute of Health, Charité - Universitätsmedizin, Berlin, GermanyVerified email at bih-charite.de
Elena CasiraghiAssociate Professor, Computer Science Department (DI), Università degli Studi di MilanoVerified email at unimi.it
Marco MesitiAssociate Professor, Università di milanoVerified email at di.unimi.it
Marco FrascaUniversity of MilanVerified email at di.unimi.it
Justin ReeseLawrence Berkeley National LabVerified email at lbl.gov
Francesco MasulliFull Professor of Computer Science, University of Genoa (ITALY)Verified email at unige.it
Christopher J MungallLawrence Berkeley National LaboratoryVerified email at lbl.gov
Melissa HaendelUniversity of North CarolinaVerified email at tislab.org
Max SchubachComputational Genome Biology, Berlin Institute of Health at Charité - Universitätsmedizin BerlinVerified email at bih-charite.de
Alberto PaccanaroProfessor at Royal Holloway, University of LondonVerified email at cs.rhul.ac.uk
Tiffany J CallahanIBM ResearchVerified email at ibm.com
Nicolò Cesa-BianchiProfessor of Computer Science, Università degli Studi di Milano and Politecnico di MilanoVerified email at unimi.it
Damian SmedleyQueen Mary University of LondonVerified email at qmul.ac.uk
Thomas DietterichDistinguished Professor (Emeritus), Computer Science, Oregon State UniversityVerified email at cs.orst.edu
Malte SpielmannInstitute of Human Genetics, University of Lübeck & Kiel UniversityVerified email at uw.edu
Vida RavanmehrBaylor College of MedicineVerified email at bcm.edu
Daniel DanisBerlin Institute of Health @ CharitéVerified email at bih-charite.de
Tiziana CastrignanòProfessor, University of Tuscia, Department of Ecological and Biological Sciences, Viterbo, Italy.Verified email at unitus.it
Giuliano ArmanoAssociate Professor of Computer Science, University of CagliariVerified email at unica.it

Giorgio Valentini

Computer Science Dept. - University of Milan

Verified email at di.unimi.it - Homepage

Bioinformatics Computational biology Machine Learning


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Ensembles of learning machines G Valentini, F Masulli Neural Nets: 13th Italian Workshop on Neural Nets, WIRN VIETRI 2002 Vietri …, 2002	504	2002
An expanded evaluation of protein function prediction methods shows an improvement in accuracy Y Jiang, TR Oron, ..., G Valentini, ..., I Friedberg, P Radivojac Genome Biology 17 (184), 2016	437	2016
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens N Zhou, Y Jiang, TR Bergquist, AJ Lee, BZ Kacsoh, AW Crocker, ... Genome biology 20, 1-23, 2019	403	2019
Bias-variance analysis of support vector machines for the development of SVM-based ensemble methods G Valentini, TG Dietterich Journal of Machine Learning Research 5 (Jul), 725-775, 2004	376	2004
A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease D Smedley, M Schubach, JOB Jacobsen, S Köhler, T Zemojtel, ... American Journal of Human Genetics 99 (3), 595-606, 2016	310	2016
True Path Rule hierarchical ensembles for genome-wide gene function prediction G Valentini Computational Biology and Bioinformatics, IEEE/ACM Transactions on 8 (3 …, 2011	171	2011
Ensemble methods: a review M Re, G Valentini Advances in Machine Learning and Data Mining for Astronomy, 563-594, 2012	152*	2012
Cancer recognition with bagged ensembles of support vector machines G Valentini, M Muselli, F Ruffino Neurocomputing 56, 461-466, 2004	129	2004
Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes JT Reese, H Blau, E Casiraghi, T Bergquist, JJ Loomba, TJ Callahan, ... EBioMedicine 87, 2023	124	2023
Fuzzy ensemble clustering based on random projections for DNA microarray data analysis R Avogadri, G Valentini Artificial Intelligence in Medicine 45 (2-3), 173-183, 2009	119	2009
Imbalance-aware machine learning for predicting rare and common disease-associated non-coding variants M Schubach, M Re, PN Robinson, G Valentini Scientific reports 7 (1), 2959, 2017	113	2017
Low bias bagged support vector machines G Valentini, TG Dietterich Proceedings of the 20th International Conference on Machine Learning (ICML …, 2003	110	2003
Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference N Cesa-Bianchi, M Re, G Valentini Machine Learning 88 (1), 209-241, 2012	103	2012
Bio-molecular cancer prediction with random subspace ensembles of support vector machines A Bertoni, R Folgieri, G Valentini Neurocomputing 63, 535-539, 2005	95	2005
An experimental bias-variance analysis of SVM ensembles based on resampling techniques G Valentini IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 35 …, 2005	87	2005
Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments E Casiraghi, D Malchiodi, G Trucco, M Frasca, L Cappelletti, T Fontana, ... IEEE Access 8, 196299-196325, 2020	84	2020
GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology H Caniza, AE Romero, S Heron, H Yang, A Devoto, M Frasca, M Mesiti, ... Bioinformatics 30 (15), 2235-2236, 2014	72	2014
Gene expression data analysis of human lymphoma using support vector machines and output coding ensembles G Valentini Artificial Intelligence in Medicine 26 (3), 281-304, 2002	72	2002
An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods G Valentini, A Paccanaro, H Caniza, AE Romero, M Re Artificial Intelligence in Medicine, 2014	71	2014
Comparing decomposition methods for classification F Masulli, G Valentini KES'2000. Fourth International Conference on Knowledge-Based Intelligent …, 2000	68	2000

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