Marco Beccuti
Associate Professor
- Dipartimento di Informatica
- SSD: INF/01 - informatics
- ORCID: orcid.org/0000-0001-6125-9460
Contacts
- +39 011 6706780
- marco.beccuti@unito.it
- https://unito.webex.com/meet/marco.beccuti
- Dipartimento di Informatica - Università degli Studi di Torino
Via Pessinetto 12, 10149 Torino, Italy - https://cmb.campusnet.unito.it/persone/marco.beccuti
- Contacts VCard
At
- Computer Science Department
- Dipartimento di Informatica
- Artificial Intelligence for Biomedicine and Healthcare
- Cellular and Molecular Biology
- Corso di laurea in Informatica
- Corso di laurea in Scienze Biologiche (L-13)
- Corso di laurea magistrale in Informatica
- Laurea Magistrale (M.Sc.) in Stochastics and Data Science
- Two - Year Master Degree in Economics
- PhD in Complex Systems for Quantitative Biomedicine
- PhD in Computer Science
Curriculum vitae
Research products
All my research productsSelected research products
- Alessandri S, Ratto ML, Rabellino S, Piacenti G, Contaldo SG, Pernice S, Beccuti M, Calogero RA, Alessandri L. (2024) CREDO: a friendly Customizable, REproducible, DOcker file generator for bioinformatics applications. BMC bioinformatics 25(1) 110 [DOI PMID]
- Arigoni M, Ratto ML, Riccardo F, Balmas E, Calogero L, Cordero F, Beccuti M, Calogero RA, Alessandri L. (2024) A single cell RNAseq benchmark experiment embedding "controlled" cancer heterogeneity. Scientific data 11(1) 159 [DOI PMID]
- Boretto C, Actis C, Faris P, Cordero F, Beccuti M, Ferrero G, Muzio G, Moccia F, Autelli R. (2023) Tamoxifen Activates Transcription Factor EB and Triggers Protective Autophagy in Breast Cancer Cells by Inducing Lysosomal Calcium Release: A Gateway to the Onset of Endocrine Resistance. International journal of molecular sciences 25(1) [DOI PMID]
- Pernice S, Maglione A, Tortarolo D, Sirovich R, Clerico M, Rolla S, Beccuti M, Cordero F. (2023) A new computational workflow to guide personalized drug therapy. Journal of biomedical informatics 148 104546 [DOI PMID]
- Pernice S, Sirovich R, Grassi E, Viviani M, Ferri M, Sassi F, Alessandri L, Tortarolo D, Calogero RA, Trusolino L, Bertotti A, Beccuti M, Olivero M, Cordero F. (2023) CONNECTOR, fitting and clustering of longitudinal data to reveal a new risk stratification system. Bioinformatics (Oxford, England) 39(5) [DOI PMID]
- Contaldo SG, Alessandri L, Colonnelli I, Beccuti M, Aldinucci M. (2023) Bringing Cell Subpopulation Discovery on a Cloud-HPC Using rCASC and StreamFlow. Methods in molecular biology (Clifton, N.J.) 2584 337-345 [DOI PMID]
- Beccuti M, Calogero RA. (2023) Single-Cell RNAseq Clustering. Methods in molecular biology (Clifton, N.J.) 2584 241-250 [DOI PMID]
- Avesani S, Viesi E, Alessandri L, Motterle G, Bonnici V, Beccuti M, Calogero R, Giugno R. (2022) Stardust: improving spatial transcriptomics data analysis through space-aware modularity optimization-based clustering. GigaScience 11 [DOI PMID]
- Alessandri L, Ratto ML, Contaldo SG, Beccuti M, Cordero F, Arigoni M, Calogero RA. (2021) Sparsely Connected Autoencoders: A Multi-Purpose Tool for Single Cell omics Analysis. International journal of molecular sciences 22(23) [DOI PMID]
- Genuardi E, Romano G, Beccuti M, Alessandria B, Mannina D, Califano C, Rota Scalabrini D, Cortelazzo S, Ladetto M, Ferrero S, Calogero RA, Cordero F. (2021) Application of the Euro Clonality next-generation sequencing-based marker screening approach to detect immunoglobulin heavy chain rearrangements in mantle cell lymphoma patients: first data from the Fondazione Italiana Linfomi MCL0208 trial. British journal of haematology 194(2) 378-381 [DOI PMID]
- Nosi V, Luca A, Milan M, Arigoni M, Benvenuti S, Cacchiarelli D, Cesana M, Riccardo S, Di Filippo L, Cordero F, Beccuti M, Comoglio PM, Calogero RA. (2021) MET Exon 14 Skipping: A Case Study for the Detection of Genetic Variants in Cancer Driver Genes by Deep Learning. International journal of molecular sciences 22(8) [DOI PMID]
- Licheri N, Bonnici V, Beccuti M, Giugno R. (2021) GRAPES-DD: exploiting decision diagrams for index-driven search in biological graph databases. BMC bioinformatics 22(1) 209 [DOI PMID]
- Alessandri L, Cordero F, Beccuti M, Arigoni M, Calogero RA. (2021) Computational Analysis of Single-Cell RNA-Seq Data. Methods in molecular biology (Clifton, N.J.) 2284 289-301 [DOI PMID]
- Ferrero G, Licheri N, De Bortoli M, Calogero RA, Beccuti M, Cordero F. (2021) Computational Analysis of circRNA Expression Data. Methods in molecular biology (Clifton, N.J.) 2284 181-192 [DOI PMID]
- Alessandri L, Cordero F, Beccuti M, Licheri N, Arigoni M, Olivero M, Di Renzo MF, Sapino A, Calogero R. (2021) Sparsely-connected autoencoder (SCA) for single cell RNAseq data mining. NPJ systems biology and applications 7(1) 1 [DOI PMID]
- Pernice S, Follia L, Maglione A, Pennisi M, Pappalardo F, Novelli F, Clerico M, Beccuti M, Cordero F, Rolla S. (2020) Computational modeling of the immune response in multiple sclerosis using epimod framework. BMC bioinformatics 21(Suppl 17) 550 [DOI PMID]
- Pernice S, Castagno P, Marcotulli L, Maule MM, Richiardi L, Moirano G, Sereno M, Cordero F, Beccuti M. (2020) Impacts of reopening strategies for COVID-19 epidemic: a modeling study in Piedmont region. BMC infectious diseases 20(1) 798 [DOI PMID]
- Castagno P, Pernice S, Ghetti G, Povero M, Pradelli L, Paolotti D, Balbo G, Sereno M, Beccuti M. (2020) A computational framework for modeling and studying pertussis epidemiology and vaccination. BMC bioinformatics 21(Suppl 8) 344 [DOI PMID]
- Ferrero G, Licheri N, Coscujuela Tarrero L, De Intinis C, Miano V, Calogero RA, Cordero F, De Bortoli M, Beccuti M. (2019) Docker4Circ: A Framework for the Reproducible Characterization of circRNAs from RNA-Seq Data. International journal of molecular sciences 21(1) [DOI PMID]
- Pernice S, Pennisi M, Romano G, Maglione A, Cutrupi S, Pappalardo F, Balbo G, Beccuti M, Cordero F, Calogero RA. (2019) A computational approach based on the colored Petri net formalism for studying multiple sclerosis. BMC bioinformatics 20(Suppl 6) 623 [DOI PMID]
- Alessandri L, Cordero F, Beccuti M, Arigoni M, Olivero M, Romano G, Rabellino S, Licheri N, De Libero G, Pace L, Calogero RA. (2019) rCASC: reproducible classification analysis of single-cell sequencing data. GigaScience 8(9) [DOI PMID]
- Follia L, Ferrero G, Mandili G, Beccuti M, Giordano D, Spadi R, Satolli MA, Evangelista A, Katayama H, Hong W, Momin AA, Capello M, Hanash SM, Novelli F, Cordero F. (2019) Integrative Analysis of Novel Metabolic Subtypes in Pancreatic Cancer Fosters New Prognostic Biomarkers. Frontiers in oncology 9 115 [DOI PMID]
- Kulkarni N, Alessandri L, Panero R, Arigoni M, Olivero M, Ferrero G, Cordero F, Beccuti M, Calogero RA. (2018) Reproducible bioinformatics project: a community for reproducible bioinformatics analysis pipelines. BMC bioinformatics 19(Suppl 10) 349 [DOI PMID]
- Coscujuela Tarrero L, Ferrero G, Miano V, De Intinis C, Ricci L, Arigoni M, Riccardo F, Annaratone L, Castellano I, Calogero RA, Beccuti M, Cordero F, De Bortoli M. (2018) Luminal breast cancer-specific circular RNAs uncovered by a novel tool for data analysis. Oncotarget 9(18) 14580-14596 [DOI PMID]
- Beccuti M, Genuardi E, Romano G, Monitillo L, Barbero D, Boccadoro M, Ladetto M, Calogero R, Ferrero S, Cordero F. (2017) HashClone: a new tool to quantify the minimal residual disease in B-cell lymphoma from deep sequencing data. BMC bioinformatics 18(1) 516 [DOI PMID]
- Beccuti M, Cordero F, Arigoni M, Panero R, Amparore EG, Donatelli S, Calogero RA. (2018) SeqBox: RNAseq/ChIPseq reproducible analysis on a consumer game computer. Bioinformatics (Oxford, England) 34(5) 871-872 [DOI PMID]
- Ferrero G, Miano V, Beccuti M, Balbo G, De Bortoli M, Cordero F. (2017) Dissecting the genomic activity of a transcriptional regulator by the integrative analysis of omics data. Scientific reports 7(1) 8564 [DOI PMID]
- Martina F, Beccuti M, Balbo G, Cordero F. (2017) Peculiar Genes Selection: A new features selection method to improve classification performances in imbalanced data sets. PloS one 12(8) e0177475 [DOI PMID]
- Miglio G, Sabatino AD, Veglia E, Giraudo MT, Beccuti M, Cordero F. (2016) A computational analysis of S-(2-succino)cysteine sites in proteins. Biochimica et biophysica acta 1864(2) 211-8 [DOI PMID]
- Munoz-Amatriain M, Lonardi S, Luo M, Madishetty K, Svensson JT, Moscou MJ, Wanamaker S, Jiang T, Kleinhofs A, Muehlbauer GJ, Wise RP, Stein N, Ma Y, Rodriguez E, Kudrna D, Bhat PR, Chao S, Condamine P, Heinen S, Resnik J, Wing R, Witt HN, Alpert M, Beccuti M, Bozdag S, Cordero F, Mirebrahim H, Ounit R, Wu Y, You F, Zheng J, Simkova H, Dolezel J, Grimwood J, Schmutz J, Duma D, Altschmied L, Blake T, Bregitzer P, Cooper L, Dilbirligi M, Falk A, Feiz L, Graner A, Gustafson P, Hayes PM, Lemaux P, Mammadov J, Close TJ. (2015) Sequencing of 15 622 gene-bearing BACs clarifies the gene-dense regions of the barley genome. The Plant journal : for cell and molecular biology 84(1) 216-27 [DOI PMID]
- Carrara M, Lum J, Cordero F, Beccuti M, Poidinger M, Donatelli S, Calogero RA, Zolezzi F. (2015) Alternative splicing detection workflow needs a careful combination of sample prep and bioinformatics analysis. BMC bioinformatics 16 Suppl 9(Suppl 9) S2 [DOI PMID]
- Fornari C, Balbo G, Halawani SM, Ba-Rukab O, Ahmad AR, Calogero RA, Cordero F, Beccuti M. (2015) A versatile mathematical work-flow to explore how Cancer Stem Cell fate influences tumor progression. BMC systems biology 9 Suppl 3(Suppl 3) S1 [DOI PMID]
- Medico E, Russo M, Picco G, Cancelliere C, Valtorta E, Corti G, Buscarino M, Isella C, Lamba S, Martinoglio B, Veronese S, Siena S, Sartore-Bianchi A, Beccuti M, Mottolese M, Linnebacher M, Cordero F, Di Nicolantonio F, Bardelli A. (2015) The molecular landscape of colorectal cancer cell lines unveils clinically actionable kinase targets. Nature communications 6 7002 [DOI PMID]
- Beccuti M, Carrara M, Cordero F, Lazzarato F, Donatelli S, Nadalin F, Policriti A, Calogero RA. (2014) Chimera: a Bioconductor package for secondary analysis of fusion products. Bioinformatics (Oxford, England) 30(24) 3556-7 [DOI PMID]
- Fornari C, Beccuti M, Lanzardo S, Conti L, Balbo G, Cavallo F, Calogero RA, Cordero F. (2014) A mathematical-biological joint effort to investigate the tumor-initiating ability of Cancer Stem Cells. PloS one 9(9) e106193 [DOI PMID]
- Carrara M, Beccuti M, Cavallo F, Donatelli S, Lazzarato F, Cordero F, Calogero RA. (2013) State of art fusion-finder algorithms are suitable to detect transcription-induced chimeras in normal tissues? BMC bioinformatics 14 Suppl 7(Suppl 7) S2 [DOI PMID]
- Cordero F, Beccuti M, Fornari C, Lanzardo S, Conti L, Cavallo F, Balbo G, Calogero R. (2013) Multi-level model for the investigation of oncoantigen-driven vaccination effect. BMC bioinformatics 14 Suppl 6(Suppl 6) S11 [DOI PMID]
- Lonardi S, Duma D, Alpert M, Cordero F, Beccuti M, Bhat PR, Wu Y, Ciardo G, Alsaihati B, Ma Y, Wanamaker S, Resnik J, Bozdag S, Luo MC, Close TJ. (2013) Combinatorial pooling enables selective sequencing of the barley gene space. PLoS computational biology 9(4) e1003010 [DOI PMID]
- Carrara M, Beccuti M, Lazzarato F, Cavallo F, Cordero F, Donatelli S, Calogero RA. (2013) State-of-the-art fusion-finder algorithms sensitivity and specificity. BioMed research international 2013 340620 [DOI PMID]
- Mayer KF, Waugh R, Brown JW, Schulman A, Langridge P, Platzer M, Fincher GB, Muehlbauer GJ, Sato K, Close TJ, Wise RP, Stein N. (2012) A physical, genetic and functional sequence assembly of the barley genome. Nature 491(7426) 711-6 [DOI PMID]
- Cordero F, Beccuti M, Donatelli S, Calogero RA. (2012) Large disclosing the nature of computational tools for the analysis of next generation sequencing data. Current topics in medicinal chemistry 12(12) 1320-30 [DOI PMID]
- Cordero F, Beccuti M, Arigoni M, Donatelli S, Calogero RA. (2012) Optimizing a massive parallel sequencing workflow for quantitative miRNA expression analysis. PloS one 7(2) e31630 [DOI PMID]
Courses
- BIOINFORMATICS (SVB0047)
Cellular and Molecular Biology - Bioinformatica (MFN0951)
Corso di laurea magistrale in Informatica - Bioinformatics and Computational Models
PhD in Complex Systems for Quantitative Biomedicine - ONC0262A Introduction to Computational Modelling and Simulations in Life Sciences (ONC0262A)
Artificial Intelligence for Biomedicine and Healthcare - Programming for Data Science (ONC0254)
Artificial Intelligence for Biomedicine and Healthcare - Python programming for data science (MAT0338)
Laurea Magistrale (M.Sc.) in Stochastics and Data Science - R Programming for data science (MAT0337)
Laurea Magistrale (M.Sc.) in Stochastics and Data Science - Systems Biomedicine Approaches to Epidemiology and public health (ONC0262)
Artificial Intelligence for Biomedicine and Healthcare
Research topics
Marco Beccuti is scientific coordinator of InfoLife National Laboratory of CINI, technical coordinator of ELIXIR Node of the Università degli Studi di Torino, scientific coordinator of the laboratory "HPC for biomed and AI" in ICxT, Chair of the Scientific Committee of the "HPC4AI" laboratory" at the Università degli Studi di Torino, and scientific co-coordinator of "Quantitative Biology" (q-Bio) group. He is also member of the "Performance Evaluation and System Validation" group (QMIPS), of "Bioinformatics ITalian Society" (BITS), and of the "Consorzio Nazionale Interuniversitario per le Telecomunicazioni" (CNIT).
His research is currently mainly focused on:
- designing FAIR (Findable, Accessible, Interoperable, Re-usable) workflows for the analysis
of deep sequencing data (i.e. genomic, transcriptomic and single cell data); - developing modeling and analysis techniques for studying complex biological systems.
Research groups
Research projects
- MICROBES-4-CLIMATE - Microbial services addressing climate change risks for biodiversity and for agricultural and forestry ecosystems: enabling curiosity-driven research and advancing frontier knowledge
- SUS-MIRRI.IT Strengthening the MIRRI Italian Research Infrastructure for Sustainable Bioscience and Bioeconomy
- TrustAlert: Empowering Public Health with Real-Time Insights and Future Preparedness
- EUMaster4HPC- EU Master in High Performance Computing
- The resilience of the Mediterranean sea to directional climate change: development of experimental and risk models to evaluate the resistance mechanism of different marine
- Creation of a computational framework to model and study West Nile Disease
- Experiments and study of models for the evaluation of Computation at the University of Turin
Activities in agenda
Academic bodies
Office hours
Si riceve previo appuntamento telefonico o via e-mail.