Matteo Ré

Marco Frasca, Alberto Bertoni, Matteo Re, Giorgio Valentini: A neural network algorithm for semi-supervised node label learning from unbalanced data. Neural Networks 43: 84-98 (2013)

Matteo Re, Giorgio Valentini: Cancer module genes ranking using kernelized score functions. BMC Bioinformatics 13(S-14): S3 (2012)

Nicolò Cesa-Bianchi, Matteo Re, Giorgio Valentini: Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference. Machine Learning 88(1-2): 209-241 (2012)

Matteo Re, Marco Mesiti, Giorgio Valentini: A Fast Ranking Algorithm for Predicting Gene Functions in Biomolecular Networks. IEEE/ACM Trans. Comput. Biology Bioinform. 9(6): 1812-1818 (2012)

Matteo Re, Giorgio Valentini: Random Walking on Functional Interaction Networks to Rank Genes Involved in Cancer. AIAI (2) 2012: 66-75

Matteo Re, Giorgio Valentini: Large Scale Ranking and Repositioning of Drugs with Respect to DrugBank Therapeutic Categories. ISBRA 2012: 225-236

Oleg Okun, Giorgio Valentini, Matteo Ré (Eds.): Ensembles in Machine Learning Applications. Studies in Computational Intelligence 373, Springer 2011, isbn 978-3-642-22909-1

Matteo Ré: Comparing early and late data fusion methods for gene expression prediction. Soft Comput. 15(8): 1497-1504 (2011)

Alberto Bertoni, Matteo Re, Francesco Saccà, Giorgio Valentini: Identification of promoter regions in genomic sequences by 1-dimensional constraint clustering. WIRN 2011: 162-169

Alessandro Rozza, Gabriele Lombardi, Matteo Re, Elena Casiraghi, Giorgio Valentini, Paola Campadelli: A Novel Ensemble Technique for Protein Subcellular Location Prediction. Ensembles in Machine Learning Applications 2011: 151-167

Matteo Re, Giorgio Valentini: Integration of heterogeneous data sources for gene function prediction using decision templates and ensembles of learning machines. Neurocomputing 73(7-9): 1533-1537 (2010)

Matteo Re, Giorgio Valentini: Noise tolerance of Multiple Classifier Systems in data integration-based gene function prediction. J. Integrative Bioinformatics 7(3) (2010)

Matteo Ré, Giorgio Valentini: Simple ensemble methods are competitive with state-of-the-art data integration methods for gene function prediction. Journal of Machine Learning Research - Proceedings Track 8: 98-111 (2010)

Matteo Re, Giorgio Valentini: An Experimental Comparison of Hierarchical Bayes and True Path Rule Ensembles for Protein Function Prediction. MCS 2010: 294-303

Matteo Ré, Giulio Pavesi: Detecting conserved coding genomic regions through signal processing of nucleotide substitution patterns. Artificial Intelligence in Medicine 45(2-3): 117-123 (2009)

Matteo Re, Graziano Pesole, David Stephen Horner: Accurate discrimination of conserved coding and non-coding regions through multiple indicators of evolutionary dynamics. BMC Bioinformatics 10: 282 (2009)

Roberto Avogadri, Matteo Brioschi, Fulvia Ferrazzi, Matteo Re, Alessandro Beghini, Giorgio Valentini: A stability-based algorithm to validate hierarchical clusters of genes. IJKESDP 1(4): 318-330 (2009)

Matteo Re, Giorgio Valentini: Ensemble Based Data Fusion for Gene Function Prediction. MCS 2009: 448-457

Matteo Re, Giorgio Valentini: Comparing early and late data fusion methods for gene function prediction. WIRN 2009: 197-207

Matteo Re, Giorgio Valentini: Prediction of Gene Function Using Ensembles of SVMs and Heterogeneous Data Sources. Applications of Supervised and Unsupervised Ensemble Methods 2009: 79-91

Paolo D'Onorio De Meo, Danilo Carrabino, Nico Sanna, Tiziana Castrignanò, Giorgio Grillo, Flavio Licciulli, Sabino Liuni, Matteo Re, Flavio Mignone, Graziano Pesole: A high performance grid-web service framework for the identification of 'conserved sequence tags'. Future Generation Comp. Syst. 23(3): 371-381 (2007)

Matteo Ré, Giulio Pavesi: Signal Processing in Comparative Genomics. WILF 2007: 544-550