MSc: 2016; M.Sc. Molecular Biotechnology and Bioinformatics, University of Milano
Email: jessica (dot) gliozzo (at) gmail (dot) com
Main interests: Bioinformatics, Machine Learning
Jessica Gliozzo is a research fellow in bioinformatics at the IRCCS Ca’ Granda – Ospedale Maggiore Policlinico of Milan and collaborates with the AnacletoLab (Bioinformatics and Computational Biology and Bioinformatics laboratory). She obtained a BSc in Medical Biotechnology at University of Milan in 2014 and MSc in Molecular Biotechnology and Bioinformatics at University of Milan in 2016. Her main research areas are bioinformatics and machine learning. She is currently working in the analysis of Next Generation Sequencing (NGS) data from patients affected by primitive hematopoietic proliferative disorders of the skin. Moreover, she is working on the development of deep learning neural networks for the prediction and prioritization of regulatory variants in human diseases and on the development of a network-based semi-supervised model able to predict the patients’ clinical outcome leveraging information from heterogenous biological data.
L. Cappelletti, J. Gliozzo, A. Petrini and G. Valentini. Training Neural Networks with Balanced Mini-batch to Improve the Prediction of Pathogenic Genomic Variants in Mendelian Diseases. Sensors & Transducers, IFSA Publishing, SL 234(6), 2019.
J. Gliozzo, P. Perlasca, M. Mesiti, E. Casiraghi, V. Vallacchi, E. Vergani, M. Frasca, G. Grossi, A. Petrini, M. Re, A. Paccanaro and G. Valentini. Network modeling of patients’ biomolecular profiles for clinical phenotype/outcome prediction. Scientific Reports, Nature Publishing, 2020.
P. Perlasca, M. Frasca, C. Ba, M. Notaro, A. Petrini, E. Casiraghi, G. Grossi, J. Gliozzo, G. Valentini and M. Mesiti. UNIPred-Web: a web tool for the integration and visualization of biomolecular networks for protein function prediction. BMC Bioinformatics, BioMed Central 20(1), 2019.
M. Frasca, G. Grossi, J. Gliozzo, M. Mesiti, M. Notaro, P. Perlasca, A. Petrini and G. Valentini. A GPU-based algorithm for fast node label learning in large and unbalanced biomolecular networks. BMC Bioinformatics, BioMed Central 19(10), 2018.
B. Barricelli, E. Casiraghi, J. Gliozzo, V. Huber, B. Leone, A. Rizzi and B. Vergani. ki67 nuclei detection and ki67-index estimation: a novel automatic approach based on human vision modeling. BMC Bioinformatics, Springer 20(1), 2019.
C. Ba, E. Casiraghi, M. Frasca, J. Gliozzo, G. Grossi, M. Mesiti, M. Notaro, P. Perlasca, A. Petrini, M. Re and Others. A Graphical Tool for the Exploration and Visual Analysis of Biomolecular Networks. International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, 2018.
J. Gliozzo, P. Perlasca, M. Mesiti, E. Casiraghi, V. Vallacchi, E. Vergani, M. Frasca, G. Grossi, A. Petrini, M. Re and Others. Network modeling of patients' biomolecular profiles for clinical phenotype/outcome prediction. Scientific reports, Nature Publishing Group 10(1), 2020.
L. Cappelletti, A. Petrini, J. Gliozzo, E. Casiraghi, M. Schubach, M. Kircher and G. Valentini. Bayesian optimization improves tissue-specific prediction of active regulatory regions with deep neural networks. International Work-Conference on Bioinformatics and Biomedical Engineering, 2020.