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Location: http://informatica.unito.it/robots.html
Location: http://informatica.unito.it/robots.html

Francesca Cordero

Professore/Professoressa associato/a

Contatti

Presso

  • 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 in Biologia dell'Ambiente
  • Dottorato in Sistemi Complessi per le Scienze della Vita (fino al ciclo 35) - PhD Programme in Complex Systems for Life Sciences (until 35th cycle)
  • PhD in Complex Systems for Quantitative Biomedicine
  • PhD in Computer Science
  • PhD Programme in Complex Systems for Life Sciences (until 35th cycle)

Prodotti della ricerca

Tutti i miei prodotti della ricerca

Prodotti della ricerca selezionati

  1. Godel M, Morena D, Ananthanarayanan P, Buondonno I, Ferrero G, Hattinger CM, Di Nicolantonio F, Serra M, Taulli R, Cordero F, Riganti C, Kopecka J. (2020) Small Nucleolar RNAs Determine Resistance to Doxorubicin in Human Osteosarcoma. International journal of molecular sciences 21(12) [DOI  PMID]
  2. Mandili G, Follia L, Ferrero G, Katayama H, Hong W, Momin AA, Capello M, Giordano D, Spadi R, Satolli MA, Evangelista A, Hanash SM, Cordero F, Novelli F. (2020) Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients. Cancers 12(3) [DOI  PMID]
  3. Tarallo S, Ferrero G, Gallo G, Francavilla A, Clerico G, Realis Luc A, Manghi P, Thomas AM, Vineis P, Segata N, Pardini B, Naccarati A, Cordero F. (2020) Correction for Tarallo et al., "Altered Fecal Small RNA Profiles in Colorectal Cancer Reflect Gut Microbiome Composition in Stool Samples". mSystems 5(1) [DOI  PMID]
  4. 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]
  5. 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]
  6. Cordero F, Calogero RA, Caselle M. (2019) BITS2018: the fifteenth annual meeting of the Italian Society of Bioinformatics. BMC bioinformatics 20(Suppl 9) 562 [DOI  PMID]
  7. Thomas AM, Manghi P, Asnicar F, Pasolli E, Armanini F, Zolfo M, Beghini F, Manara S, Karcher N, Pozzi C, Gandini S, Serrano D, Tarallo S, Francavilla A, Gallo G, Trompetto M, Ferrero G, Mizutani S, Shiroma H, Shiba S, Shibata T, Yachida S, Yamada T, Wirbel J, Schrotz-King P, Ulrich CM, Brenner H, Arumugam M, Bork P, Zeller G, Cordero F, Dias-Neto E, Setubal JC, Tett A, Pardini B, Rescigno M, Waldron L, Naccarati A, Segata N. (2019) Author Correction: Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation. Nature medicine 25(12) 1948 [DOI  PMID]
  8. Tarallo S, Ferrero G, Gallo G, Francavilla A, Clerico G, Realis Luc A, Manghi P, Thomas AM, Vineis P, Segata N, Pardini B, Naccarati A, Cordero F. (2019) Altered Fecal Small RNA Profiles in Colorectal Cancer Reflect Gut Microbiome Composition in Stool Samples. mSystems 4(5) [DOI  PMID]
  9. 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]
  10. Thomas AM, Manghi P, Asnicar F, Pasolli E, Armanini F, Zolfo M, Beghini F, Manara S, Karcher N, Pozzi C, Gandini S, Serrano D, Tarallo S, Francavilla A, Gallo G, Trompetto M, Ferrero G, Mizutani S, Shiroma H, Shiba S, Shibata T, Yachida S, Yamada T, Wirbel J, Schrotz-King P, Ulrich CM, Brenner H, Arumugam M, Bork P, Zeller G, Cordero F, Dias-Neto E, Setubal JC, Tett A, Pardini B, Rescigno M, Waldron L, Naccarati A, Segata N. (2019) Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation. Nature medicine 25(4) 667-678 [DOI  PMID]
  11. 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]
  12. Iannello A, Rolla S, Maglione A, Ferrero G, Bardina V, Inaudi I, De Mercanti S, Novelli F, D'Antuono L, Cardaropoli S, Todros T, Turrini MV, Cordioli C, Puorro G, Marsili A, Lanzillo R, Brescia Morra V, Cordero F, De Bortoli M, Durelli L, Visconti A, Cutrupi S, Clerico M. (2018) Pregnancy Epigenetic Signature in T Helper 17 and T Regulatory Cells in Multiple Sclerosis. Frontiers in immunology 9 3075 [DOI  PMID]
  13. 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]
  14. Allione A, Pardini B, Viberti C, Giribaldi G, Turini S, Di Gaetano C, Guarrera S, Cordero F, Oderda M, Allasia M, Gontero P, Sacerdote C, Vineis P, Matullo G. (2018) MMP23B expression and protein levels in blood and urine are associated with bladder cancer. Carcinogenesis 39(10) 1254-1263 [DOI  PMID]
  15. Pardini B, Cordero F, Naccarati A, Viberti C, Birolo G, Oderda M, Di Gaetano C, Arigoni M, Martina F, Calogero RA, Sacerdote C, Gontero P, Vineis P, Matullo G. (2018) microRNA profiles in urine by next-generation sequencing can stratify bladder cancer subtypes. Oncotarget 9(29) 20658-20669 [DOI  PMID]
  16. 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]
  17. Ferrero G, Cordero F, Tarallo S, Arigoni M, Riccardo F, Gallo G, Ronco G, Allasia M, Kulkarni N, Matullo G, Vineis P, Calogero RA, Pardini B, Naccarati A. (2018) Small non-coding RNA profiling in human biofluids and surrogate tissues from healthy individuals: description of the diverse and most represented species. Oncotarget 9(3) 3097-3111 [DOI  PMID]
  18. 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]
  19. 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]
  20. 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]
  21. 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]

Insegnamenti

Temi di ricerca

Tutor per il Dottorato in Informatica

Interests

  • Computational Biology;
  • Cancer genomics and Epigenomics;
  • Evolutionary Genomics and Modelling;
  • Mathematical models for cancer progression and treatment response;
  • High-throughput technologies: develop of algorithms to analyze Next-Generation Sequencing;
  • Systems Biology;

 



Deep sequencing algorithms
I am interested in the definition of new algorithms and workflow with different purposes: deconvolution for assembly of new genomes, mapping, analysis of RNA-seq, microRNA, ChIP-seq, structural genomics variations detection etc. The results deriving from the application of these algorithms was applied in the genome sequencing project of Hordeum vulgare.

Application of mathematical approaches to oncology
I work on the study of cancer through the application of mathematical models. In particular, I am focus on a specific set of tumors whose growth and progression are influenced by a small subpopulation of cancer cells, known as Cancer Stem Cells (CSCs). I am interested in the study of tumor growth through a multi-level modeling approach considering the dynamics occurring among the different subpopulations of cells, and regulatory networks describing key cellular events in tumorigenesis. Moreover I investigate the application of model fitting techniques of cancer volume data and the integration of these data with the genomic and transcriptomic knowledge in the study of clonal and mutational evolution of cancer.

Systems Biology

Quantitative analysis and Reverse engineering of cellular systems
I work on the development of a methodology that allows to perform qualitative and quantitative analysis of a selected portion of signal transduction events involved in angiogenesis process.
This approach is based on the use of Petri Nets (PN) and in some cases their variant called Stochastic Petri Nets (SPNs), that provide a detailed representation of the biological model. Moreover a simplification process is applied in order to obtain a model where the number of parameters is reduced and the analysis results tractable from the computational point of view.
Moreover I have worked on the development of a object-oriented methodology, based on the Mean Field Analysis, that offers an intuitive way to describe the behavior of biological systems characterized by a huge number of interacting objects.

Gruppi di ricerca

Progetti di ricerca

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Ultimo aggiornamento: 31/10/2024 11:34
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