Dottorando in Fisica , 39o ciclo (2023-2026)
Dipartimento Scienza Applicata e Tecnologia (DISAT)
Profilo
Dottorato di ricerca
Argomento di ricerca
Statistical-physics inspired learning of the protein sequence universe
Tutori
Keywords
Biografia
I completed a Master Double degree International path on Physics of Complex Systems of Politecnico di Torino. The International path of the Master Program is based in prestigious sites in Italy and France. For my master internship I modeled the stochastic dynamics of protein evolution (composed of mutations and selection) using approaches
inspired by statistical physics at LCQB in Sorbonne Universitè in Paris.
Now, I undergo a PhD on "Generative interpretable models of the protein Universe". The program is a cotutela with Sorbonne Universitè in Paris. Basically, I develop interpretable machine learning/statistical models to study how proteins evolve in time and interact between each other.
Pubblicazioni
Pubblicazioni più recenti Vedi tutte le pubblicazioni su Porto@Iris
- Rossi, Saverio; Di Bari, Leonardo; Weigt, Martin; Zamponi, Francesco (2025)
Fluctuations and the limit of predictability in protein evolution. In: REPORTS ON PROGRESS IN PHYSICS, vol. 88, pp. 1-15. ISSN 0034-4885
Contributo su Rivista - Di Bari, L.; Bisardi, M.; Cotogno, S.; Weigt, M.; Zamponi, F. (2024)
Emergent time scales of epistasis in protein evolution. In: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, vol. 121, pp. 1-10. ISSN 0027-8424
Contributo su Rivista