My activity at the CNR is primarily in the biomedical field and in scientific communication. I got a PhD in Biochemistry and Molecular Biology and have acquired expertise in bioinformatics, omics sciences, and molecular diagnostics over the years. My work involves developing effective solutions for analysing complex data for clinical applications, such as identifying early disease biomarkers. My specific field of study concerns non-coding RNAs, with a particular focus on the role of miRNAs in mechanisms related to the onset and development of diseases. In this field, I study tumours, ageing, and neurodegenerative diseases. In a long-standing collaboration with the Department of Computer Science at the University of Bari, I have contributed to the development of machine learning-based models and tools for analysing complex molecular regulatory networks. These models aim to elucidate physiological and pathological molecular mechanisms through the integration of large amounts of molecular data from large-scale studies. Currently residing in Bari, I collaborate with national and international networks to promote translational science. My goal is to optimise biomedical research results to provide easily applicable, cost-effective, and non-invasive solutions for early diagnosis, disease progression, or even as tools for monitoring therapeutic efficacy. Another area of application I have been working on for several years, in collaboration with CREA (Council for Agricultural Research and Analysis of Agricultural Economics) in Turi, is the study of the nutritional properties of table grapes. I have developed a nutrigenomics study on healthy subjects and am currently analysing comparative transcriptomics data to identify nutritionally more valuable table grape varieties.
Research Activities
Transcriptomic profiling for coding and non-coding RNAs biomarker discovery and regulatory pathway analysis
Transcriptomic profiling of tumor extracellular vesicles (EVs) as intercellular communication mediators and for liquid biopsy and drug delivery applications
Transcriptomic analysis of peripheral blood cells to assess changes in gene expression triggered by specific dietary patterns or nutrients.
Development of bioinformatics tools for Big Data analysis.
Application of advanced statistical methods, machine learning, deep learning, explainable AI (XAI), and data mining for predicting pathological mechanisms, identifying disease biomarkers and supporting patient stratification.
