CURRENT POSITION(S)

• Tenure-track Researcher (“RTD-B”), Dept. of Informatics, Systems and Communications (DISCo), Univ. of Milan-Bicocca. https://www.disco.unimib.it/it
• Co-head of the Data and Computational Biology Lab, Univ. of Milan-Bicocca
• Director of the Lake Como School of Advanced Studies on Cancer Development and Complexity. https://cdac2021.lakecomoschool.org/
• Member of the B4 Bicocca Bioinformatics, Biostatistics and Bioimaging Centre, Milan, Italy

PUBLICATION RECAP

• Indexed publications: 61 (Scopus), 33 as first, last or corresponding author (update 1-apr-22)
• Overall citations: 1196 (Scholar) 710 (Scopus)
• H-index: 19 (Scholar) 16 (Scopus)
• i-10 index: 33 (Scholar)

Research keywords: data science, artificial intelligence, bioinformatics, computational biology, complex systems, cancer/viral evolution.

SELECTED PUBBLICATIONS (20)

• Angaroni F, Chen K, Damiani C, Caravagna G, Graudenzi A, Ramazzotti D (2022). PMCE: efficient inference of expressive models of cancer evolution with high prognostic power. BIOINFORMATICS, vol. 38, p. 754-762, ISSN: 1367-4803, doi: 10.1093/bioinformatics/btab717
• Ramazzotti, Daniele, Angaroni, Fabrizio, Maspero, Davide, Ascolani, Gianluca, Castiglioni, Isabella, Piazza, Rocco, Antoniotti, Marco, Graudenzi, Alex (2022). LACE: Inference of cancer evolution models from longitudinal single-cell sequencing data. JOURNAL OF COMPUTATIONAL SCIENCE, vol. 58, 101523, ISSN: 1877-7503, doi: 10.1016/j.jocs.2021.101523
• Ramazzotti, Daniele, Angaroni, Fabrizio, Maspero, Davide, Mauri, Mario, D’Aliberti, Deborah, Fontana, Diletta, Antoniotti, Marco, Elli, Elena Maria, Graudenzi, Alex, Piazza, Rocco (2022). Large-Scale Analysis of SARS-CoV-2 Synonymous Mutations Reveals the Adaptation to the Human Codon Usage During the Virus Evolution. VIRUS EVOLUTION, ISSN: 2057-1577, doi: 10.1093/ve/veac026
• Graudenzi A., Maspero D., Angaroni F., Piazza R., Ramazzotti D. (2021). Mutational signatures and heterogeneous host response revealed via large-scale characterization of SARS-CoV-2 genomic diversity. ISCIENCE, vol. 24, 102116, ISSN: 2589-0042, doi: 10.1016/j.isci.2021.102116
• Maspero, Davide, Angaroni, Fabrizio, Porro, Danilo, Piazza, Rocco, Graudenzi, Alex, Ramazzotti, Daniele (2021). VirMutSig: Discovery and assignment of viral mutational signatures from sequencing data. STAR PROTOCOLS, vol. 2, 100911, ISSN: 2666-1667, doi: 10.1016/j.xpro.2021.100911
• Patruno, L, Maspero, D, Craighero, F, Angaroni, F, Antoniotti, M, Graudenzi, A (2021). A review of computational strategies for denoising and imputation of single-cell transcriptomic data. BRIEFINGS IN BIOINFORMATICS, vol. 22, bbaa222, ISSN: 1467-5463, doi: 10.1093/bib/bbaa222
• Ramazzotti. , Daniele, Angaroni, Fabrizio, Maspero, Davide, Gambacorti-Passerini, Carlo, Antoniotti, Marco, Graudenzi, Alex, Piazza, Rocco (2021). VERSO: a comprehensive framework for the inference of robust phylogenies and the quantification of intra-host genomic diversity of viral samples. PATTERNS, vol. 2, 100212, ISSN: 2666-3899, doi: 10.1016/j.patter.2021.100212
• Angaroni, Fabrizio, Graudenzi, Alex, Rossignolo, Marco, Maspero, Davide, Calarco, Tommaso, Piazza, Rocco, Montangero, Simone, Antoniotti, Marco (2020). An Optimal Control Framework for the Automated Design of Personalized Cancer Treatments. FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, vol. 8, 523, ISSN: 2296-4185, doi: 10.3389/fbioe.2020.00523
• Damiani, C, Rovida, L, Maspero, D, Sala, I, Rosato, L, Di Filippo, M, Pescini, D, Graudenzi, A, Antoniotti, M, Mauri, G (2020). MaREA4Galaxy: metabolic reaction enrichment analysis and visualization of RNA-seq data using Galaxy. COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, vol. 18, p. 993-999, ISSN: 2001-0370, doi: 10.1016/j.csbj.2020.04.008
• Damiani, C, Maspero, D, Di Filippo, M, Colombo, R, Pescini, D, Graudenzi, A, Westerhoff HV, Alberghina, L, Vanoni, M, Mauri, G (2019). Integration of single-cell RNA-seq data into population models to characterize cancer metabolism. PLOS COMPUTATIONAL BIOLOGY, vol. 15, e1006733, ISSN: 1553-7358, doi: 10.1371/journal.pcbi.1006733
• Ramazzotti D, Graudenzi A, De Sano L, Antoniotti M, Caravagna G (2019). Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data. BMC BIOINFORMATICS, vol. 20, p. 1-13, ISSN: 1471-2105, doi: 10.1186/s12859-019-2795-4
• Ramazzotti, Daniele, Nobile, Marco S., Antoniotti, Marco, Graudenzi, Alex (2019). Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena. JOURNAL OF COMPUTATIONAL SCIENCE, vol. 30, p. 1-10, ISSN: 1877-7503, doi: 10.1016/j.jocs.2018.10.009
• Graudenzi, A, Maspero,D, Di Filippo,M, Gnugnoli,M, Isella,C, Mauri,G, Medico,E, Antoniotti,M, Damiani,C (2018). Integration of transcriptomic data and metabolic networks in cancer samples reveals highly significant prognostic power. JOURNAL OF BIOMEDICAL INFORMATICS, vol. 87, p. 37-49, ISSN: 1532-0464, doi: 10.1016/j.jbi.2018.09.010
• Caravagna, G, GRAUDENZI, ALEX, Ramazzotti, D, Sanz Pamplona, R, De Sano, L, MAURI, GIANCARLO, Moreno, V, ANTONIOTTI, MARCO, Mishra, B. (2016). Algorithmic methods to infer the evolutionary trajectories in cancer progression. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, vol. 113, p. E4025-E4034, ISSN: 1091-6490, doi: 10.1073/pnas.1520213113
• De Sano, L, CARAVAGNA, GIULIO, RAMAZZOTTI, DANIELE, GRAUDENZI, ALEX, MAURI, GIANCARLO, Mishra, B, ANTONIOTTI, MARCO (2016). TRONCO: An R package for the inference of cancer progression models from heterogeneous genomic data. BIOINFORMATICS, vol. 32, p. 1911-1913, ISSN: 1367-4803, doi: 10.1093/bioinformatics/btw035
• RAMAZZOTTI, DANIELE, CARAVAGNA, GIULIO, Olde Loohuis, L, GRAUDENZI, ALEX, Korsunsky, I, MAURI, GIANCARLO, ANTONIOTTI, MARCO, Mishra, B. (2015). CAPRI: Efficient Inference of Cancer Progression Models from Cross-sectional Data. BIOINFORMATICS, vol. 31, p. 3016-3026, ISSN: 1367-4803, doi: 10.1093/bioinformatics/btv296
• GRAUDENZI, ALEX, CARAVAGNA, GIULIO, De Matteis, G, ANTONIOTTI, MARCO (2014). Investigating the relation between stochastic differentiation and homeostasis in intestinal crypts via multiscale modeling. PLOS ONE, vol. 9, e97272, ISSN: 1932-6203, doi: 10.1371/journal.pone.0097272
• De Matteis, G, GRAUDENZI, ALEX, ANTONIOTTI, MARCO (2013). A review of spatial computational models for multi-cellular systems, with regard to intestinal crypts and colorectal cancer development. JOURNAL OF MATHEMATICAL BIOLOGY, vol. 66, p. 1409-1462, ISSN: 0303-6812, doi: 10.1007/s00285-012-0539-4
• Graudenzi A, Serra R, Villani M, Damiani C, Colacci A, Kauffman S (2011). Dynamical properties of a Boolean model of gene regulatory network with memory. JOURNAL OF COMPUTATIONAL BIOLOGY, vol. 18, p. 1291-1303, ISSN: 1066-5277, doi: 10.1089/cmb.2010.0069
• Serra, R, Villani, M, Graudenzi, A, Kauffman, SA (2007). Why a simple model of genetic regulatory networks describes the distribution of avalanches in gene expression data. JOURNAL OF THEORETICAL BIOLOGY, vol. 246, p. 449-460, ISSN: 0022-5193, doi: 10.1016/j.jtbi.2007.01.012

Scopus profile: https://www.scopus.com/authid/detail.uri?authorId=25121540100