Duccio Cavalieri

Biography

The undersigned Duccio Cavalieri, Associate Professor at the Department of Biology since 1 November 2015, University Researcher since 01/01/2004, at the University of Florence, First Range Researcher and Coordinator of the Department of Computational Biology of the Center of Research and Innovation (CRI) of the Edmund Mach Foundation (FEM), San Michele all'Adige, Trento, from 01/04/2012 to 31/03/2015, having come to expectation without any allowances under art. 7 L. 240 / 30.12.2010. Knightshas shown as a young person a high capacity for resource and dynamism retrieval. He has obtained the following scholarships and research contracts, Ph.D. in Genetics, University of Pavia: from 31 October 1994 to 31 October 1997, Post PhD, 1997 Department of Animal Biology and Genetics "Leo Pardi", Laboratory of Mario Polsinelli, University of Florence. Coordinated and Continuing Collaboration Agreement, Catania Research Consortium, Plant Pathology Laboratory, Prof. Antonino Catara, from 8-7-1998 to 9-6-1999. Graduate Doctorate at the Organismic and Evolutionary Biology Department, Harvard University, Daniel Hartl Laboratory, from October 16, 1999 to September 3, 2001. Knights also held the following positions with corresponding academic titles: Group Leader, Laboratory Chief, Harvard University USA (Harvard University USA) from 03/09/2001 to 30/09/2004, Harvard Genomics Fellow, Molecular and Cellular Biology Department, Center for Genomics Research. Researcher at the PHARMACY faculty for SSD BIO / 19 from 29/12/2003 to 30/03/2012. Prof. Aggregate at the University of Florence from 01/11/2004 to 10/06/2011.

Research Interest

particular interest were the studies on the interaction between microorganisms, immune system and diet with the aim of understanding the rules that guide the tolerance and pathogenicity of microorganisms. Within these studies, since 2002, Cavalieri has also contributed to developing bioinformatics methods to analyze "omica" data in the context of metabolic signal transduction networks, using bioinformatics and large data screening for the definition of their bioactive properties.