Quantitative Biology (q-Bio)
Staff
- Cordero Prof.ssa Francesca (Group leader)
- Beccuti Prof. Marco (Group leader)
- Calogero Prof. Raffaele Adolfo (Affiliate)
- Ferrero Dott. Giulio (Postdoc)
- Follia Dott.ssa Laura (Postdoc)
- Piaggeschi Giulia (PhD student)
- Pernice Dott. Simone (PhD student)
- Licheri Nicola (PhD student)
- Nosi Vladimir (PhD student)
Contacts

Activity
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)
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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
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Next Generation Sequencing: Whole Genome Sequencing Library Preparation at the European Molecular Biology Laboratory (EMBL) Heidelberg (Germany) 15-19 Feb 2016.
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RNA-seq analysis, Turin (To be define)
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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
Publications
Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients
CANCERS, 2020
Pregnancy epigenetic signature in T helper 17 and T regulatory cells in multiple sclerosis
FRONTIERS IN IMMUNOLOGY, 2019
Integrative Analysis of Novel Metabolic Subtypes in Pancreatic Cancer Fosters New Prognostic Biomarkers
FRONTIERS IN ONCOLOGY, 2019
Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation
NATURE MEDICINE, 2019
rCASC: reproducible classification analysis of single-cell sequencing data
GIGASCIENCE, 2019
Altered Fecal Small RNA Profiles in Colorectal Cancer Reflect Gut Microbiome Composition in Stool Samples
MSYSTEMS, 2019
Docker4Circ: A Framework for the Reproducible Characterization of circRNAs from RNA-Seq Data
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2019
Luminal breast cancer-specific circular RNAs uncovered by a novel tool for data analysis
ONCOTARGET, 2018
A review of the deterministic and diffusion approximations for stochastic chemical reaction networks
REACTION KINETICS, MECHANISMS AND CATALYSIS, 2018
microRNA profiles in urine by next-generation sequencing can stratify bladder cancer subtypes
ONCOTARGET, 2018
Reproducible bioinformatics project: A community for reproducible bioinformatics analysis pipelines
BMC BIOINFORMATICS, 2018
MMP23B expression and protein levels in blood and urine are associated with bladder cancer
CARCINOGENESIS, 2018
Overcoming the Lack of Kinetic Information in Biochemical Reactions Networks
PERFORMANCE EVALUATION REVIEW, 2017
Dissecting the genomic activity of a transcriptional regulator by the integrative analysis of omics data
SCIENTIFIC REPORTS, 2017
SeqBox: RNAseq/ChIPseq reproducible analysis on a consumer game computer
BIOINFORMATICS, 2017
Peculiar genes selection: A new features selection method to improve classification performances in imbalanced data sets
PLOS ONE, 2017
HashClone: a new tool to quantify the minimal residual disease in B-cell lymphoma from deep sequencing data
BMC BIOINFORMATICS, 2017
Small non-coding RNA profiling in human biofluids and surrogate tissues from healthy inpiduals: Description of the perse and most represented species
ONCOTARGET, 2017
Luminal long non-coding RNAs regulated by estrogen receptor alpha in a ligand-independent manner show functional roles in breast cancer
ONCOTARGET, 2016
Biologic Data of Cynomolgus Monkeys Maintained under Laboratory Conditions
PLOS ONE, 2016
A computational analysis of S-(2-succino)cysteine sites in proteins
BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS, 2016
NETTAB 2014: From high-throughput structural bioinformatics to integrative systems biology
BMC BIOINFORMATICS, 2016
Exploiting flow equivalent server in transient analysis
COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2016
The molecular landscape of colorectal cancer cell lines unveils clinically actionable kinase targets
NATURE COMMUNICATIONS, 2015
Alternative splicing detection workflow needs a careful combination of sample prep and bioinformatics analysis
BMC BIOINFORMATICS, 2015
A versatile mathematical work-flow to explore how Cancer Stem Cell fate influences tumor progression
BMC SYSTEMS BIOLOGY, 2015
Approximate analysis of biological systems by hybrid switching jump diffusion
THEORETICAL COMPUTER SCIENCE, 2015
Sequencing of 15 622 gene-bearing BACs clarifies the gene-dense regions of the barley genome
PLANT JOURNAL, 2015
Post-treatment recovery of suboptimal DNA repair capacity and gene expression levels in colorectal cancer patients
MOLECULAR CARCINOGENESIS, 2015
Differentially methylated microRNAs in prediagnostic samples of subjects who developed breast cancer in the european prospective investigation into nutrition and cancer (EPIC-Italy) cohort
CARCINOGENESIS, 2015
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)
2019
Deriving Symbolic Ordinary Differential Equations from Stochastic Symmetric Nets Without Unfolding
Computer Performance Engineering,
European Workshop on Performance Engineering
2018
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
2018
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
2018
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)
2018
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
2018
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
2017
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
2017
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
2017
A mathematical model to study breast cancer growth
2017 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM),
IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM)
2017
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
2017
Abstract 4431: Urine microRNA profiling in bladder cancer by next-generation sequencing
Cancer Research,
American Association for Cancer Research Annual Meeting 2017
2017
Scrible: Ultra-accurate error-correction of pooled sequenced reads
Lecture Notes in Computer Science,
15th International Workshop on Algorithms in Bioinformatics, WABI 2015
2015
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
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.
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.