Silvio Bicciato

Centre for Mechanics of Biological Materials - University of Padova 
tel +39 049 8275544 - fax +39 049 8275555 - e-mail silvio.bicciato[at]


Date of birth: February 08, 1967

Silvio Bicciato is assistant professor of Industrial Bioengineering at Faculty of Biosciences and Biotechnologies, University of Modena and Reggio Emilia. His principal research interest is the design and application of database-mining algorithms based on statistical analysis, pattern recognition, and artificial neural networks, and bioinformatics tools for the analysis of molecular data from high-throughput technologies. He is the scientific coordinator of the bioinformatics unit in several projects funded by national and international institutions (MIUR FIRB, MIUR COFIN, OncoSuisse). He is the PI of Progetto di Eccellenza 2006 “A computational approach to the study of skeletal muscle genomic expression in health and disease” funded by Fondazione Cassa di Risparmio di Padova e Rovigo. He is author of more than 50 publications on international journals, books and proceedings of international conferences. He serves in the Editorial Board of Cancer Informatics.

Educational activity
He is giving the classes of Bioinformatics (basic and advanced) at the School of Biotechnologies of the University of Modena and Reggio Emilia and the classes of Cellular Bioengineering and Bioengineering for Genomics at the School of Bioengineering at the University of Padova.

Main Research Topics
Bioinformatics and computational methods for the analysis of high-throughput molecular signals.

Membership and Appointment
Society for Biological Engineering



[max 10 publications
in the last 3 years]

Ferrari F, Bortoluzzi S, Coppe A, Sirota A, Safran M, Shmoish M, Ferrari S, Lancet D, Danieli GA, Bicciato S. Novel definition files for human GeneChips based on GeneAnnot. BMC Bioinformatics. 2007 Nov 15;8:446.

Ferrari F, Bortoluzzi S, Coppe A, Basso D, Bicciato S, Zini R, Gemelli C, Danieli GA, Ferrari S. Genomic expression during human myelopoiesis. BMC Genomics. 2007 Aug 3;8:264.

Fabris S, Ronchetti D, Agnelli L, Baldini L, Morabito F, Bicciato S, Basso D, Todoerti K, Lombardi L, Lambertenghi-Deliliers G, Neri A. Transcriptional features of multiple myeloma patients with chromosome 1q gain. Leukemia. 2007 May;21(5):1113-6

Lombardi L, Poretti G, Mattioli M, Fabris S, Agnelli L, Bicciato S, Kwee I, Rinaldi A, Ronchetti D, Verdelli D, Lambertenghi-Deliliers G, Bertoni F, Neri A. Molecular characterization of human multiple myeloma cell lines by integrative genomics: insights into the biology of the disease. Genes Chromosomes Cancer. 2007 Mar;46(3):226-38.

Gallina G, Dolcetti L, Serafini P, De Santo C, Marigo I, Colombo MP, Basso G, Brombacher F, Borrello I, Zanovello P, Bicciato S, Bronte V. Tumors induce a subset of inflammatory monocytes with immunosuppressive activity on CD8+ T cells. J Clin Invest. 2006 Oct;116(10):2777-90.

Callegaro A, Basso D, Bicciato S. A locally adaptive statistical procedure (LAP) to identify differentially expressed chromosomal regions. Bioinformatics. 2006 Nov 1;22(21):2658-66.

Zangrando A, Luchini A, Buldini B, Rondelli R, Pession A, Bicciato S, te Kronnie G, Basso G. Immunophenotype signature as a tool to define prognostic subgroups in childhood acute myeloid leukemia. Leukemia. 2006 May;20(5):888-91.

Callegaro A, Spinelli R, Beltrame L, Bicciato S, Caristina L, Censuales S, De Bellis G, Battaglia C. Algorithm for automatic genotype calling of single nucleotide polymorphisms using the full course of TaqMan real-time data. Nucleic Acids Res. 2006 Apr 14;34(7):e56.

Orabona C, Puccetti P, Vacca C, Bicciato S, Luchini A, Fallarino F, Bianchi R, Velardi E, Perruccio K, Velardi A, Bronte V, Fioretti MC, Grohmann U. Toward the identification of a tolerogenic signature in IDO-competent dendritic cells. Blood. 2006 Apr 1;107(7):2846-54.

Agnelli L, Bicciato S, Mattioli M, Fabris S, Intini D, Verdelli D, Baldini L, Morabito F, Callea V, Lombardi L, Neri A. Molecular classification of multiple myeloma: a distinct transcriptional profile characterizes patients expressing CCND1 and negative for 14q32 translocations. J Clin Oncol. 2005 Oct 10;23(29):7296-306.





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