Vai al contenuto principale
Coronavirus: aggiornamenti per la comunità universitaria / Coronavirus: updates for UniTo Community
Group picture

Quantitative Biology (q-Bio)




The main interest of the Quantitative Biology (q-Bio) group is the development of computational models able to integrate several source of data and knowledge in order to give new insights in the comprehension of the biological mechanisms at the bases of the disease considered and in the definition of patient tailored therapies.

We are focus on two main research areas: the development of new algorithms to the deep sequencing data analysis and cancer modeling.

For what concern deep sequencing data, we defined new algorithms, workflow, and tools (eg SeqMDD, DSGen, HashFilter) with different purposes: deconvolution for assembly of new genomes, mapping, analysis of RNA-seq data in term of expression (i) detection of isoforms, long noncodingRNA, microRNA expression levels and (ii) discovering of chimeras. We have also experience in the analysis of CHiP-seq data and histonic modification high-throughput data, with this data available our interest is the development of new integrative approaches.

The application of our computational methodologies regards several research areas i.e. molecular oncology in particular in the study of clonal evolution, in particular in the case of immunoglobulin (IG) and T-cell receptor (TCR) gene rearrangements used for discrimination between normal (polyclonal) and abnormal/ malignant (monoclonal), detection of expression and methylation profiles of microRNAs to define a set of cancer biomarkers in colorectal cancer, bladder cancer and cervix cancer.

The cancer clonality is also investigated by mathematical and computational formalisms. We are interested in deep understanding of all the mechanisms underlying the kinetics of biochemical reactions characterizing biological pathways, in terms of concentration of substrates and products as well as rates of reactions.

We work in the definition and development of methods that allow the description of biological systems and their qualitative and quantitative analysis. The models are built through systems of differential equations and/or stochastic and deterministic computational formalisms. We are focus on the development of mathematical models that describe different stages of development and cancer progression as well as the simulation of specific therapies. In addition, we are interested in the composition of models on different time scales and granularity, eg. molecular, cellular, metabolomics, cell population level etc.

Ongoing research projects

  • Integrative approach for small RNA and microbioma biomarkers detection in colorectal cancer

LILT association 24 months (Principal Investigator) 

  • Deciphering intratumor heterogeneity in epithelial ovarian cancer using patient derived xenografts 

    AICR-IG 2016 36 months  (Bioinformatics tasks)

  • Unliganded estrogen receptor alpha AICR-IG 2015 36 months (Bioinformatics tasks)

Completed projects

  • Next Generation Sequencing platform for targeted Personalized Therapy of Leukemia, 2012, 36 months, 7th European Framework Program
  • Epigen, 2011, 36 months, Flagship Program

Next Courses

  • Next Generation Sequencing: Whole Genome Sequencing Library Preparation at the European Molecular Biology Laboratory (EMBL) Heidelberg (Germany) 15-19 Feb 2016.

  • RNA-seq analysis, Turin (To be define)

  • Whole Transcriptome Data Analysis at the European Molecular Biology Laboratory (EMBL) Heidelberg (Germany) 28 June-1 July 2016.

Past Courses

  •  Advanced Course of Whole transcriptome data analysis at the European Molecular Biology Laboratory (EMBL) Heidelberg (Germany). June 2013, June 2014, June 2015, September 2015.
  • Advanced Course of "NGS data analisys" in Jagiellonian University Medical College, Faculty of Medicine, Krakow, Poland, November 2015.
  •  Advanced Course of RNA-seq analysis in the RNA-seq Workshop, Dept. Clinical and Biological Sciences, Molecular Biotechnology Center, Torino (Italy). From March 2012, March 2013, March 2014, March 2015.
  •  Data Analysis Workshop GeneChip EXON 1.0 ST array Practical Data Analysis Course Department of clinical and biological sciences (Italy). From 2008 to 2011.

Dr. Chiara Fornari, now at AstraZeneca Cambridge UK

Francesca Cordero

+39 0116706773


 Giorgia Mandili, Laura Follia, Giulio Ferrero, Hiroyuki Katayama, Wang Hong 5, Amin A. Momin, Michela Capello, Daniele Giordano, Rosella Spadi, Maria Antonietta Satolli, Andrea Evangelista, Samir M. Hanash, Francesca Cordero, Francesco Novelli

Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients

 CANCERS,  2020

 Andrea Iannello, Simona Rolla, Alessandro Maglione, Giulio Ferrero, Valentina Bardina, Ilenia Inaudi, Stefania De Mercanti, Francesco Novelli, Lucrezia D'Antuono, Simona Cardaropoli, Tullia Todros, Maria Vittoria Turrini, Cinzia Cordioli, Giorgia Puorro, Angela Marsili, Roberta Lanzillo, Vincenzo Brescia Morra, Francesca Cordero, Michele De Bortoli, Luca Durelli, Andrea Visconti, Santina Cutrupi, Marinella Clerico

Pregnancy epigenetic signature in T helper 17 and T regulatory cells in multiple sclerosis


 Follia, Laura; Ferrero, Giulio; Mandili, Giorgia; Beccuti, Marco; Giordano, Daniele; Spadi, Rosella; Satolli, Maria Antonietta; Evangelista, Andrea; Katayama, Hiroyuki; Hong, Wang; Momin, Amin A.; Capello, Michela; Hanash, Samir M.; Novelli, Francesco; Cordero, Francesca

Integrative Analysis of Novel Metabolic Subtypes in Pancreatic Cancer Fosters New Prognostic Biomarkers


 Thomas, Andrew Maltez; Manghi, Paolo; Asnicar, Francesco; Pasolli, Edoardo; Armanini, Federica; Zolfo, Moreno; Beghini, Francesco; Manara, Serena; Karcher, Nicolai; Pozzi, Chiara; Gandini, Sara; Serrano, Davide; Tarallo, Sonia; Francavilla, Antonio; Gallo, Gaetano; Trompetto, Mario; Ferrero, Giulio; Mizutani, Sayaka; Shiroma, Hirotsugu; Shiba, Satoshi; Shibata, Tatsuhiro; Yachida, Shinichi; Yamada, Takuji; Wirbel, Jakob; Schrotz-King, Petra; Ulrich, Cornelia M; Brenner, Hermann; Arumugam, Manimozhiyan; Bork, Peer; Zeller, Georg; Cordero, Francesca; Dias-Neto, Emmanuel; Setubal, João Carlos; Tett, Adrian; Pardini, Barbara; Rescigno, Maria; Waldron, Levi; Naccarati, Alessio; Segata, Nicola

Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation


 Alessandrì, Luca; Cordero, Francesca; Beccuti, Marco; Arigoni, Maddalena; Olivero, Martina; Romano, Greta; Rabellino, Sergio; Licheri, Nicola; De Libero, Gennaro; Pace, Luigia; Calogero, Raffaele A

rCASC: reproducible classification analysis of single-cell sequencing data


 Tarallo, Sonia; Ferrero, Giulio; Gallo, Gaetano; Francavilla, Antonio; Clerico, Giuseppe; Realis Luc, Alberto; Manghi, Paolo; Thomas, Andrew Maltez; Vineis, Paolo; Segata, Nicola; Pardini, Barbara; Naccarati, Alessio; Cordero, Francesca

Altered Fecal Small RNA Profiles in Colorectal Cancer Reflect Gut Microbiome Composition in Stool Samples

 MSYSTEMS,  2019

 Ferrero, Giulio; Licheri, Nicola; Coscujuela Tarrero, Lucia; De Intinis, Carlo; Miano, Valentina; Calogero, Raffaele Adolfo; Cordero, Francesca; De Bortoli, Michele; Beccuti, Marco

Docker4Circ: A Framework for the Reproducible Characterization of circRNAs from RNA-Seq Data


 Tarrero, Lucia Coscujuela; Ferrero, Giulio; Miano, Valentina; De Intinis, Carlo; Ricci, Laura; Arigoni, Maddalena; Riccardo, Federica; Annaratone, Laura; Castellano, Isabella; Calogero, Raffaele A.; Beccuti, Marco; Cordero, Francesca; De Bortoli, Michele

Luminal breast cancer-specific circular RNAs uncovered by a novel tool for data analysis


 Mozgunov, Pavel; Beccuti, Marco; Horvath, Andras; Jaki, Thomas; Sirovich, Roberta; Bibbona, Enrico*

A review of the deterministic and diffusion approximations for stochastic chemical reaction networks


 Pardini Barbara, Cordero Francesca, Naccarati Alessio, Viberti Clara, Birolo Giovanni, Oderda Marco, Di Gaetano Cornelia, Arigoni Maddalena, Martina Federica, Calogero Raffaele, Sacerdote Carlotta, Gontero Paolo, Vineis Paolo, Matullo Giuseppe

microRNA profiles in urine by next-generation sequencing can stratify bladder cancer subtypes


 Neha Kulkarni, Luca Alessandrì, Riccardo Panero, Maddalena Arigoni, Martina Olivero, Giulio Ferrero, Francesca Cordero, Marco Beccuti, Raffaele A. Calogero

Reproducible bioinformatics project: A community for reproducible bioinformatics analysis pipelines


 Allione, Alessandra; Pardini, Barbara; Viberti, Clara; Giribaldi, Giuliana; Turini, Stefano; Di Gaetano, Cornelia; Guarrera, Simonetta; Cordero, Francesca; Oderda, Marco; Allasia, Marco; Gontero, Paolo; Sacerdote, Carlotta; Vineis, Paolo; Matullo, Giuseppe

MMP23B expression and protein levels in blood and urine are associated with bladder cancer


 Totis Niccolo; Follia Laura; Riganti Chiara; Novelli Francesco; Cordero Francesca; Beccuti Marco; Balbo Gianfranco.

Overcoming the Lack of Kinetic Information in Biochemical Reactions Networks


 Ferrero, Giulio; Miano, Valentina; Beccuti, Marco; Balbo, Gianfranco; De Bortoli, Michele; Cordero, Francesca

Dissecting the genomic activity of a transcriptional regulator by the integrative analysis of omics data


 Beccuti, Marco; Cordero, Francesca; Arigoni, Maddalena; Panero, Riccardo; Amparore, Elvio G; Donatelli, Susanna; Calogero, Raffaele A.

SeqBox: RNAseq/ChIPseq reproducible analysis on a consumer game computer


 Martina, Federica; Beccuti, Marco; Balbo, Gianfranco; Cordero, Francesca

Peculiar genes selection: A new features selection method to improve classification performances in imbalanced data sets

 PLOS ONE,  2017

 Beccuti, Marco; Genuardi, Elisa; Romano, Greta; Monitillo, Luigia; Barbero, Daniela; Boccadoro, Mario; Ladetto, Marco; Calogero, Raffaele; Ferrero, Simone; Cordero, Francesca

HashClone: a new tool to quantify the minimal residual disease in B-cell lymphoma from deep sequencing data


 Ferrero, Giulio; Cordero, Francesca; Tarallo, Sonia; Arigoni, Maddalena; Riccardo, Federica; Gallo, Gaetano; Ronco, Guglielmo; Allasia, Marco; Kulkarni, Neha; Matullo, Giuseppe; Vineis, Paolo; Calogero, Raffaele A.; Pardini, Barbara; Naccarati, Alessio

Small non-coding RNA profiling in human biofluids and surrogate tissues from healthy inpiduals: Description of the perse and most represented species


 Miano, Valentina; Ferrero, Giulio; Reineri, Stefania; Caizzi, Livia; Annaratone, Laura; Ricci, Laura; Cutrupi, Santina; Castellano, Isabella; Cordero, Francesca; De Bortoli, Michele

Luminal long non-coding RNAs regulated by estrogen receptor alpha in a ligand-independent manner show functional roles in breast cancer


 Rosso, Marilena Caterina; Badino, Paola; Ferrero, Giulio; Costa, Roberto; Cordero, Francesca; Steidler, Stephanie

Biologic Data of Cynomolgus Monkeys Maintained under Laboratory Conditions

 PLOS ONE,  2016

 Miglio, Gianluca; Sabatino, Alessandro Damiano; Veglia, Eleonora; Giraudo, Maria Teresa; Beccuti, Marco; Cordero, Francesca

A computational analysis of S-(2-succino)cysteine sites in proteins


 Romano, Paolo; Cordero, Francesca

NETTAB 2014: From high-throughput structural bioinformatics to integrative systems biology


 Angius, Alessio; Horvath, Andras; Halawani, Sami M.; Ba-Rukab, Omar M.; Ahmad, Ab Rahman; Balbo, Gianfranco .

Exploiting flow equivalent server in transient analysis


 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; # #co-last and corresponding; Bardelli, A

The molecular landscape of colorectal cancer cell lines unveils clinically actionable kinase targets


 Carrara, Matteo; Lum, Josephine; Cordero, Francesca; Beccuti, Marco; Poidinger, Michael; Donatelli, Susanna; Calogero, Raffaele; Zolezzi, Francesca

Alternative splicing detection workflow needs a careful combination of sample prep and bioinformatics analysis


 Fornari, Chiara; Balbo, Gianfranco; Halawani, Sami M; Ba-Rukab, Omar; Ahmad, Ab; Calogero, Raffaele A; Cordero, Francesca; Beccuti, Marco

A versatile mathematical work-flow to explore how Cancer Stem Cell fate influences tumor progression


 Angius Alessio; Balbo Gianfranco; Beccuti Marco; Bibbona Enrico; Horvath Andras; Sirovich Roberta

Approximate analysis of biological systems by hybrid switching jump diffusion


 Muñoz-Amatriaín, María; Lonardi, Stefano; Luo, Mingcheng; Madishetty, Kavitha; Svensson, Jan T.; Moscou, Matthew J.; Wanamaker, Steve; Jiang, Tao; Kleinhofs, Andris; Muehlbauer, Gary J.; Wise, Roger P.; Stein, Nils; Ma, Yaqin; Rodriguez, Edmundo; Kudrna, Dave; Bhat, Prasanna R.; Chao, Shiaoman; Condamine, Pascal; Heinen, Shane; Resnik, Josh; Wing, Rod; Witt, Heather N.; Alpert, Matthew; Beccuti, Marco; Bozdag, Serdar; Cordero, Francesca; Mirebrahim, Hamid; Ounit, Rachid; Wu, Yonghui; You, Frank; Zheng, Jie; Simková, Hana; Dolezel, Jaroslav; Grimwood, Jane; Schmutz, Jeremy; Duma, Denisa; Altschmied, Lothar; Blake, Tom; Bregitzer, Phil; Cooper, Laurel; Dilbirligi, Muharrem; Falk, Anders; Feiz, Leila; Graner, Andreas; Gustafson, Perry; Hayes, Patrick M.; Lemaux, Peggy; Mammadov, Jafar; Close, Timothy J.

Sequencing of 15 622 gene-bearing BACs clarifies the gene-dense regions of the barley genome


 Slyskova, Jana; Cordero, Francesca; Pardini, Barbara; Korenkova, Vlasta; Vymetalkova, Veronika; Bielik, Ludovit; Vodickova, Ludmila; Pitule, Pavel; Liska, Vaclav; Matejka, Vit Martin; Levy, Miroslav; Buchler, Tomas; Kubista, Mikael; Naccarati, Alessio; Vodicka, Pavel

Post-treatment recovery of suboptimal DNA repair capacity and gene expression levels in colorectal cancer patients


 Cordero, Francesca; Ferrero, Giulio; Polidoro, Silvia; Fiorito, Giovanni; Campanella, Gianluca; Sacerdote, Carlotta; Mattiello, Amalia; Masala, Giovanna; Agnoli, Claudia; Frasca, Graziella; Panico, Salvatore; Palli, Domenico; Krogh, Vittorio; Tumino, Rosario; Vineis, Paolo; Naccarati, Alessio

Differentially methylated microRNAs in prediagnostic samples of subjects who developed breast cancer in the european prospective investigation into nutrition and cancer (EPIC-Italy) cohort


 Gallo, G.; Tarallo, S.; Cordero, F.; Pardini, B.; Ferrero, G.; Vineis, P.; Clerico, G.; Realis Luc, A.; Naccarati, A.; Trompetto, M.

Next-generation sequencing for miRNA profiling of stool and plasma samples of patients with colorectal cancer or precancerous lesions


 Catarsi, P; Cordero, F; Ferrero, G; Beccuti, M; Poletto, V; Bonetti, E; Villani, L; Massa, M; Fois, G; Campanelli, R; Magrini, U; Rosti, V; Barosi, G

Deregulated Genes in Hematopoietic Stem Cells Isolated from Spleen of Patients with Myelofibrosis

 BLOOD,  2016

 Marco Beccuti, Lorenzo Capra, Massimiliano De Pierro, Giuliana Franceschinis, Laura Follia, Simone Pernice

A Tool for the Automatic Derivation of Symbolic ODE from Symmetric Net Models

 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), 

 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)


 Marco Beccuti, Lorenzo Capra, Massimiliano De Pierro, Giuliana Franceschinis, Simone Pernice

Deriving Symbolic Ordinary Differential Equations from Stochastic Symmetric Nets Without Unfolding

 Computer Performance Engineering, 

 European Workshop on Performance Engineering


 Pernice S., Beccuti M., Do P., Pennisi M., Pappalardo F.

Estimating Daclizumab effects in Multiple Sclerosis using Stochastic Symmetric Nets

 Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018, 

 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018


 Kordon F.; Garavel H.; Hillah L.M.; Paviot-Adet E.; Jezequel L.; Hulin-Hubard F.; Amparore E.; Beccuti M.; Berthomieu B.; Evrard H.; Jensen P.G.; Le Botlan D.; Liebke T.; Meijer J.; Srba J.; Thierry-Mieg Y.; van de Pol J.; Wolf K.

MCC’2017 – The Seventh Model Checking Contest

 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 

 The Seventh Model Checking Contest


 Amparore E.G.; Donatelli S.; Beccuti M.; Garbi G.; Miner A.

Decision Diagrams for Petri Nets: A Comparison of Variable Ordering Algorithms

 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 

 International Workshop on Petri Nets and Software Engineering (PNSE 2017)


 Amparore E.G.; Beccuti M.; Botta M.; Donatelli S.; Tango F.

Adaptive artificial co-pilot as enabler for autonomous vehicles and intelligent transportation systems

 CEUR Workshop Proceedings, 

 10th International Workshop on Agents in Traffic and Transportation, ATT 2018


 Ballarini, Paolo; Beccuti, Marco*; Bibbona, Enrico; Horvath, Andras; Sirovich, Roberta; Sproston, Jeremy

Analysis of timed properties using the jump-diffusion approximation

 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 

 14th European Workshop on Computer Performance Engineering, EPEW 2017


 Amparore Elvio Gilberto ; Beccuti Marco ; Donatelli Susanna

Gradient-Based Variable Ordering of Decision Diagrams for Systems with Structural Units

 Automated Technology for Verification and Analysis, 

 ATVA: 15th International Symposium on Automated Technology for Verification and Analysis


 Amparore, E. G., Donatelli, S., Beccuti, M., Garbi, G., Miner Andrew

Decision diagrams for Petri nets: which variable ordering?

 Proceedings of the International Workshop on Petri Nets and Software Engineering (PNSE'17),, 

 PNSE 2017 Petri Nets and Software Engineering


 Chivassa, G; Fornari, C; Sirovich, R; Pennisi, M; Beccuti, M; Cordero, F

A mathematical model to study breast cancer growth


 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM)


 Totis, Niccolò; Beccuti, Marco; Cordero, Francesca; Follia, Laura; Riganti, Chiara; Novelli, Francesco; Balbo, Gianfranco

Dealing with indetermination in biochemical networks

 VALUETOOLS'16 proceedings of the 10th EAI International Conference on Performance Evaluation Methodologies and Tools on 10th EAI International Conference on Performance Evaluation Methodologies and Tools, 

 10th EAI International Conference on Performance Evaluation Methodologies and Tools, ValueTools 2016


 Pardini, Barbara; Cordero, Francesca; Naccarati, Alessio; Ferrero, Giulio; Viberti, Clara; Oderda, Marco; Arigoni, Maddalena; Calogero, Raffaele; Sacerdote, Carlotta; Gontero, Paolo; Vineis, Paolo; Matullo, Giuseppe

Abstract 4431: Urine microRNA profiling in bladder cancer by next-generation sequencing

 Cancer Research, 

 American Association for Cancer Research Annual Meeting 2017


 Duma, Denise; Cordero, Francesca; Beccuti, Marco; Ciardo, Gianfranco; Close, Timothy J.; Lonardi, Stefano

Scrible: Ultra-accurate error-correction of pooled sequenced reads

 Lecture Notes in Computer Science, 

 15th International Workshop on Algorithms in Bioinformatics, WABI 2015


 Duma, Denise; Cordero, Francesca; Beccuti, Marco; Ciardo, Gianfranco; Close, Timothy J.; Lonardi, Stefano

Scrible: Ultra-accurate error-correction of pooled sequenced reads

 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 

 15th International Workshop on Algorithms in Bioinformatics, WABI 2015


Peculiar Genes Selection: a New Features Selection Method to Improve Classification Performances in Imbalanced Data Sets

PGS - CODE       PGS - Data and Command

RefGen version 1.0

Given a set of experiments this algorithm takes as input a list of genomic intervals, and it returns a reference defined by the genomic positions which are spanned by more than τ intervals.

RefGen - CODE

NormChIP version 1.0

This algorithm adopts the DESeq normalization method on ChIP-x signal profiles computed within a set of genomic regions of interest.


Last update: 05/08/2022 14:16
Non cliccare qui!