GRAUDENZI ALEX

CURRENT POSITIONS

• Tenure-track Researcher (“RTD-B”), Dept. of Informatics, Systems and Communications (DISCo), Univ. of Milan-Bicocca. Scientific Area (SSD): INF-01 Informatics
• Co-head of the Data and Computational Biology Lab, Univ. of Milan-Bicocca. https://dcb.disco.unimib.it/people/graudenzi-alex/
• 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

TRACK RECORD (update July 22)

• 68 indexed publications (Scopus), 38 of which as first, last or corresponding author 
  • Citations: 1270+ (Scholar) 775+ (Scopus)
  • H-index: 19 (Scholar) 16 (Scopus)
  • i-10 index: 36 (Scholar)
  • Scopus: https://www.scopus.com/authid/detail.uri?authorId=25121540100
  • Google scholar: https://scholar.google.com/citations?hl=it&user=FtHxbLIAAAAJ
• Involved in 10+ funded national and international projects 
• Patents: co-author of US Patent US11205519B2 
• Invited speaker at 6 international conferences/seminars
• Peer-reviewed contributions at 15+ international conferences
• Member of the program and organizing committees of 25+ international conferences (1 as chair).
• Member of the editorial board of 3 international journals: Cancer Informatics, Frontiers in Genetics (Computational Genomics) and Frontiers in Applied Mathematics and Statistics (Mathematical Biology)
• Visiting scientist at New York University (US), New York Genome Center (US), University of Toronto (Canada), Catalan Institute of Oncology (Spain), Universidade NOVA de Lisboa (Portugal).
• Peer reviewer for 15+ international journals (https://publons.com/wos-op/researcher/1303966/alex-graudenzi/peer-review/) 
• Co-developer of 15+ software tools for bioinformatics and computational biology: https://github.com/BIMIB-DISCo
• Supervisor of 3 PhD students in Computer Science and 1 PostDoc.

(MAIN) RESEARCH AREAS

• Computational methods for cancer and viral evolution
• Data science for health and medicine
• Multiscale modeling and simulation of biological systems
• Bioinformatics methods for multi-omics (single-cell) data analysis and integration
• Explainable AI and deep learning

ACTIVE PROJECTS

• 2021 – 2025: AIRC Investigator grant (IG): “ANAKIN” Advanced Nanotechnology to Assist Keeping the tumor microenvironment Involved in cancer Neutralization (PI: Miriam Colombo – Univ. of Milan-Bicocca). Role: collaborator (0.5 man/year 2024-2025).
• 2019 – 2024: My First AIRC Grant: “Integrating pharmacogenomic and pharmacometabolomic data towards personalized opioid therapies for cancer pain” (PI: Francesca Colombo - ITB-CNR). Role: collaborator.
• 2019 – 2022: Call HUB Resarch and Innovation, Regione Lombardia, POR FESR 2014-2020 project “INTERSLA” Innovation, new technological models and networks to treat ALS (PI: Giuseppe Lauria Pinter – IRCSS Istituto Neurologico "Carlo Besta"). Role: co-responsible of WP4: Bioinformatics techniques for the analysis and integration of clinical big data (1140 hours).
• 2018 – 2023: CRUK/AIRC/AECC Accelerator Award “SCCEIC” Single-cell cancer evolution in the clinic (PI: Giovanni Tonon - IRCCS Ospedale San Raffaele.). Role: co-responsible of Programme 3: Bioinformatics analysis, single-cell data integration and evolutionary methods.
• 2016 –: ESFRI/MIUR project SysBioNet (Director: Lilia Alberghina – Univ. of Milan-Bicocca) Role: collaborator.

SELECTED PUBBLICATIONS (20)

1. Ramazzotti, D., Angaroni, F., Maspero, D., Ascolani, G., Castiglioni, I., Piazza, R., Antoniotti, M., Graudenzi, A. (2022) Variant calling from scRNA-seq data allows the assessment of cellular identity in patient-derived cell lines. NATURE COMMUNICATIONS, 13 (1), art. no. 2718. doi: 10.1038/s41467-022-30230-w
2. Angaroni, F., Guidi, A., Ascolani, G., d’Onofrio, A., Antoniotti, M., Graudenzi, A. (2022) J-SPACE: a Julia package for the simulation of spatial models of cancer evolution and of sequencing experiments. BMC BIOINFORMATICS, 23 (1), art. no. 269. doi: 10.1186/s12859-022-04779-8
3. Mella, L., Lal, A., Angaroni, F., Maspero, D., Piazza, R., Sidow, A., Antoniotti, M., Graudenzi, A., Ramazzotti, D. (2022) SparseSignatures: An R package using LASSO-regularized non-negative matrix factorization to identify mutational signatures from human tumor samples. STAR PROTOCOLS, 3 (3), art. no. 101513. doi: 10.1016/j.xpro.2022.101513
4. Calabretta, E., Guidetti, A., Ricci, F., Di Trani, M., Monfrini, C., Magagnoli, M., Bramanti, S., Maspero, D., Morello, L., Merli, M., Di Rocco, A., Graudenzi, A., Derenzini, E., Antoniotti, M., Rossi, D., Corradini, P., Santoro, A., Carlo-Stella, C. (2022) Chemotherapy after PD-1 inhibitors in relapsed/refractory Hodgkin lymphoma: Outcomes and clonal evolution dynamics. BRITISH JOURNAL OF HEMATOLOGY, 198 (1), pp. 82-92. doi: 10.1111/bjh.18183
5. Ramazzotti, D., Maspero, D., Angaroni, F., Spinelli, S., Antoniotti, M., Piazza, R., Graudenzi, A. (2022) Early detection and improved genomic surveillance of SARS-CoV-2 variants from deep sequencing data. ISCIENCE, 25 (6), art. no. 104487. doi: 10.1016/j.isci.2022.104487
6. 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
7. 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
8. 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
9. 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
10. 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
11. 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
12. 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
13. 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
14. 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
15. 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
16. 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
17. 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
18. 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
19. 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
20. 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

DIDACTICS

• Responsible lecturer for 10+ courses in bachelor’s and master’s degrees at the Univ. of Modena and Reggio Emilia and at the Univ. of Milan-Bicocca
• Active courses:
  • Foundations of Computer Science (1st year, Bachelor Degree in Computer Science)
  • Programming 1 (1st year, bachelor's Degree in Computer Science)
  • Data Analytics (2nd year, master's Degree in Computer Science)
• Responsible lecturer at 1 II level master's degree in Methods and Data Analysis in Biomedical Research