Stefano De Pretis

Post Doc

Research Lines

Genomic Science




Center for Genomic Science, Via Adamello 16, Milano



  • Postdoc, Center for Genomic Science, Istituto Italiano di Tecnologia, Milan, Italy. (2012-present)
  • System Administrator, Graal Informatics, Milan, Italy. (2009)
  • Research fellow, Ronzoni Institute for Chemical and Biochemical Research, Milan, Italy. (2005)


  • PhD, Bioinformatics, Università del Sannio, 2012 (Visiting student at Harvard Medical School, 2011-2012)
  • MS, Bioinformatics, Università degli Studi di Milano-Bicocca, 2008
  • BS, Molecular Biotechnology, Università degli Studi di Milano-Bicocca, 2005

Thesis works

  • Dynamical systems in the fate decision of Embryonic Stem Cells: the role of excitability and bistability. (Prof. Giancarlo Mauri)
  • Stochastic Simulations with MesoRD and their applications on small Genetic Networks. (Prof. Luca De Gioia)
  • NMR Studies of Characterization of Low-Molecular-Weight Heparins. (Dr. Marco Guerrini)


RNA metabolism and modification

RNA polymerase recruitment and progression dynamics 

Myc oncogene biology

Implications of RNA metabolism in Cancer biology

IIT Publications

  • 2020
  • Furlan M.iit, Tanaka I.iit, Leonardi T.iit, de Pretis S.iit, Pelizzola M.iit

    Direct RNA Sequencing for the Study of Synthesis, Processing, and Degradation of Modified Transcripts

    Frontiers in Genetics, vol. 11
  • 2019
  • Tesi A.iit, de Pretis S.iit, Furlan M.iit, Filipuzzi M., Morelli M.J.iit, Andronache A.iit, Doni M., Verrecchia A., Pelizzola M.iit, Amati B., Sabo A.

    An early Myc-dependent transcriptional program orchestrates cell growth during B-cell activation

    EMBO Reports, vol. 20, (no. 9)
  • Furlan M.iit, Galeota E.iit, de Pretis S.iit, Caselle M., Pelizzola M.iit

    M6A-dependent RNA dynamics in T cell differentiation

    Genes, vol. 10, (no. 1)
  • 2017
  • De Pretis S.iit, Kress T.R.iit, Morelli M.J.iit, Sabo A.iit, Locarno C.iit, Verrecchia A., Doni M., Campaner S.iit, Amati B.iit, Pelizzola M.iit

    Integrative analysis of RNA polymerase II and transcriptional dynamics upon MYC activation

    Genome Research, vol. 27, (no. 10), pp. 1658-1664
  • Mukherjee N., Calviello L., Hirsekorn A., De Pretis S.iit, Pelizzola M.iit, Ohler U.

    Integrative classification of human coding and noncoding genes through RNA metabolism profiles

    Nature Structural and Molecular Biology, vol. 24, (no. 1), pp. 86-96
  • 2016
  • Marzi M.J.iit, Ghini F.iit, Cerruti B.iit, De Pretis S.iit, Bonetti P.iit, Giacomelli C.iit, Gorski M.M., Kress T.iit, Pelizzola M.iit, Muller H.iit, Amati B.iit, Nicassio F.iit

    Degradation dynamics of micrornas revealed by a novel pulse-chase approach

    Genome Research, vol. 26, (no. 4), pp. 554-565
  • Marzi M. J., Ghini F., Cerruti B., de Pretis S.iit, Nicassio F.iit

    Insights into function and regulation of microRNAs by decoding degradation dynamics

    Keystone Symposia: Small RNA Silencing: Little Guides, Big Biology (A6)
  • Bianchi V.iit, Ceol A.iit, Ogier A.G.E., De Pretis S.iit, Galeota E.iit, Kishore K.iit, Bora P.iit, Croci O.iit, Campaner S.iit, Amati B.iit, Morelli M.J.iit, Pelizzola M.iit

    Integrated systems for NGS data management and analysis: Open issues and available solutions

    Frontiers in Genetics, vol. 7, (no. MAY)
  • Melloni G.E.M.iit, de Pretis S.iit, Riva L.iit, Pelizzola M.iit, Ceol A.iit, Costanza J.iit, Muller H.iit, Zammataro L.iit

    LowMACA: Exploiting protein family analysis for the identification of rare driver mutations in cancer

    BMC Bioinformatics, vol. 17, (no. 1)
  • 2015
  • De Pretis S.iit, Kress T.iit, Morelli M.J.iit, Melloni G.E.M.iit, Riva L.iit, Amati B.iit, Pelizzola M.iit

    INSPEcT: A computational tool to infer mRNA synthesis, processing and degradation dynamics from RNA- and 4sU-seq time course experiments

    Bioinformatics, vol. 31, (no. 17), pp. 2829-2835
  • Kishore K.iit, de Pretis S.iit, Lister R., Morelli M.J.iit, Bianchi V.iit, Amati B.iit, Ecker J.R., Pelizzola M.iit

    methylPipe and compEpiTools: A suite of R packages for the integrative analysis of epigenomics data

    BMC Bioinformatics, vol. 16, (no. 1)
  • Pelizzola M.iit, Morelli M.J.iit, Sabo A.iit, Kress T.R.iit, de Pretis S.iit, Amati B.iit

    Selective transcriptional regulation by Myc: Experimental design and computational analysis of high-throughput sequencing data

    Data in Brief, vol. 3, pp. 40-46
  • Austenaa L.M.I., Barozzi I., Simonatto M., Masella S., Della Chiara G., Ghisletti S., Curina A., de Wit E., Bouwman B.A.M., de Pretis S.iit, Piccolo V., Termanini A., Prosperini E., Pelizzola M.iit, de Laat W., Natoli G.

    Transcription of Mammalian cis-Regulatory Elements Is Restrained by Actively Enforced Early Termination

    Molecular Cell, vol. 60, (no. 3), pp. 460-474
  • 2014
  • de Pretis S.iit, Pelizzola M.iit

    Computational and experimental methods to decipher the epigenetic code

    Frontiers in Genetics, vol. 5, (no. SEP)
  • Melloni G.E.M.iit, Ogier A.G.E., de Pretis S.iit, Mazzarella L., Pelizzola M.iit, Pelicci P.G., Riva L.iit

    DOTS-Finder: A comprehensive tool for assessing driver genes in cancer genomes

    Genome Medicine, vol. 6, (no. 6)
  • Sabo A.iit, Kress T.R.iit, Pelizzola M.iit, De Pretis S.iit, Gorski M.M., Tesi A.iit, Morelli M.J.iit, Bora P.iit, Doni M., Verrecchia A., Tonelli C., Faga G., Bianchi V.iit, Ronchi A.iit, Low D., Muller H.iit, Guccione E., Campaner S.iit, Amati B.iit

    Selective transcriptional regulation by Myc in cellular growth control and lymphomagenesis

    Nature, vol. 511, (no. 7510), pp. 488-492