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Marianyela Petrizzelli
Principal Data Scientist - AI for Precision Medicine
Experience
Principal Data Scientist - AI for Precision Medicine
(January 2023 - Present)
Sanofi Digital R&D, R&D Data and Computational Science
• Developed Shiny/Streamlit applications for exploration of complex single-cell results (e.g., ligand-receptor interactions, gene regulatory networks, differentially expressed genes, gene ontologies, patient stratification).
• Trained foundation single-cell large language models (scLLMs) with publicly and/or internally available single-cell datasets to build disease-associated scLLMs.
• Applied cutting-edge ML and AI techniques for the analysis of large complex (multimodal) omics datasets.
• Proposed and supervised a master’s-level internship on a Computational Systems Biology project.
• Leveraged collaborations both internally and externally to accelerate biomarker discovery.
• Adopted the Agile way of working.
Keywords: Generative AI, Single-cell omics data, Immuno-oncology.
Postdoctoral Researcher
(September 2019 - January 2023)
Institut Curie, PSL Research University, INSERM U900, MINES ParisTech, F-75006 Paris, France.
• Performed advanced statistical analysis of large complex omics datasets.
• Developed methods for multi-level data representation (multi-level networks) and integration (e.g., https://github.com/iPC-project-H2020/ipcrg/tree/master/scripts/data-driven_relational_graphs).
• Designed pipelines to analyze interaction networks of statistical associations among features (genes) and similarity networks among observations (patients).
• Created pipelines that integrate machine learning and optimization techniques to model cell metabolism.
• Produced a data catalog containing links to Ewing sarcoma omics datasets (https://sysbio-curie.github.io/EwSOmicsAtlas/index.html).
• Collaborated with biologists, computational biologists, engineers, and physicists within the H2020-ICT-2018-2 individualized Pediatric Cure project to design algorithms that address cancer-specific questions.
Keywords: Network reconstruction and analysis, Investigation of potency mesures, Mathematical modeling.
Junior lecturer and assistant professor
(September 2018 - Present)
Université Paris Descartes
• I was responsible of the evaluation of my students.
• I managed class activities to enhance learning.
• I participate to the internship’s jury of my students.
Keywords: Mathematics, Applied statistics, Probability.
Junior lecturer and assistant professor
(September 2016 - August 2018)
IUT d'Orsay
Keywords: Analysis, trigonometry and complex numbers, Python, Data analysis.
Research intern
(January 2015 - April 2015)
Institut National de Recherche Agronomique – GQE – Le Moulon
Second-year master research internship in population genetics, under the supervision of O. Martin.
• I developed a general model able to calculate the probabilities of multi-locus genotypes in brother and sister mating.
• I constructed the associated algorithm in R. I showed a practical application of the model for data imputation.
Education
Doctor of Philosophy in
(2015 - 2019)
Life-science
Institution:
Université Paris-Saclay
• I lead this interdisciplinary project at the interface between mathematics, statistics, and biology. It involved modeling and analysis of complex biological data. I performed multivariate analysis and clustering considering the cross design on which the data was measured. I constructed a unique statistical model and performed clustering analysis to disentangle hybrid vigor and inbreeding depression.
• I proposed a novel model to predict metabolic fluxes from proteomics data which involved an integrative approach. Keywords: modeling, data analysis, data mining, machine learning, bio-statistics, genetics, big data, hybrid vigor, inbreeding, diallel design, constraint-based model, metabolism, yeast
Master degree in
(2013 - 2015)
Physics of complex systems
Institution:
Politecnico of Turin
The course was organized in four semesters: 1° semester in Trieste at SISSA and ICTP. 2° semester in Torino at Politecnico di Torino University. 3° semester in Paris at a consortium involving Universities Pierre et Marie Curie, Paris Diderot, Paris Sud and the Ecole Normale Superieure. 4° semester was devoted to a research stage and to the European multidisciplinary Spring College in Trieste at ICTP.
Master Thesis: “Multilocus probabilities in the presence of genetic recombination“.
Bachelor degree in
(2009 - 2013)
Mathematics
Institution:
University of Trento
Bachelor Thesis: “On the Preisach model for hysteresis: from the deterministic case to the stochastic one”.
- Acknowledged in the international review @ Fiévet J.B., Nidelet T., Dillmann C. and de Vienne D. Heterosis Is a Systemic Property Emerging From Non-linear Genotype-Phenotype Relationships: Evidence From in Vitro Genetics and Computer Simulations.
- Acknowledged in the international review @ Raffoux X., Bourge M., Dumas F., Martin O.C. and Falque M. Role of Cis, Trans, and Inbreeding Effects on Meiotic Recombination in Saccharomyces cerevisiae.
- KITP Graduate Fellow @ Kavli Institute of Theoretical Physics, University of Santa Barbara, CA.
Publications Permalink
- Petrizzelli M., Coton C., de Vienne D.. Formalising the law of diminishing returns in metabolic networks using an electrical analogy. Research Square, 2023. . doi.org/10.21203/rs.3.rs-3580603/v1.
- Petrizzelli M., de Vienne D., Nidelet T., Noûs C. and Dillmann C. Data integration uncovers the metabolic bases of phenotypic variation in yeast. PLOS Computational Biology, 2021. issn:17(7): e1009157. doi:10.1371/journal.pcbi.1009157.
- Núñez-Carpintero I., Petrizzelli M., Zinovyev A., Cirillo D. and Valencia A.. The multilayer community structure of medulloblastoma. iScience, 2021. issn:2589-0042. doi:10.1016/j.isci.2021.102365.
- Petrizzelli M., Merlevede J. and Zinovyev A. Systems Biology Analysis for Ewing Sarcoma. Springer US, 2021. isbn:978-1-0716-1020-6. doi:10.1007/978-1-0716-1020-6_23.
- Jebreen K., Petrizzelli M. and Martin O.C. Probabilities of Multilocus Genotypes in SIB Recombinant Inbred Lines. Frontiers in Genetics, 2019. issn:1664-8021. doi:10.3389/fgene.2019.00833.
- Petrizzelli M., de Vienne D. and Dillmann C. Decoupling the Variances of Heterosis and Inbreeding Effects Is Evidenced in Yeast’s Life-History and Proteomic Traits. Genetics, 2019. issn:0016-6731, 1943-2631. doi:10.1534/genetics.118.301635.
- Petrizzelli M. Mathematical modelling and integration of complex biological data : analysis of the heterosis phenomenon in yeast. PhD thesis, 2019. . 2019SACLS204.