Summary
Barbara Bravi obtained her PhD in Applied Mathematics (Biological and Statistical Physics) at King’s College London under the supervision of Peter Sollich, working on path integral approaches to subnetwork description and inference for biochemical stochastic processes. She was then postdoctoral researcher at École Politechnique Fédérale de Lausanne (supervised by Matthieu Wyart) and subsequently at École Normale Supérieure de Paris (supervised by Simona Cocco, Rémi Monasson, Thierry Mora, Aleksandra Walczak). In her postdoctoral research, she investigated and developed statistical frameworks of inference to model different examples of protein functions: protein allostery, i.e., the regulation between distant sites in proteins (at École Politechnique Fédérale de Lausanne); the protein-protein binding mechanisms underlying immune responses at the molecular level (at École Normale Supérieure de Paris). She joined the Department of Mathematics as Lecturer in Biomathematics in October 2021.
Barbara’s research focusses on statistical inference methods for biological systems, in particular methods to reconstruct dynamics of biological networks and the sequence-function mapping in proteins; currently, an area of particular interest to her is immunology. More broadly, Barbara’s research directions include: mathematical modelling of stochastic biochemical reactions and model reduction strategies for complex networks; machine learning, data science and their biomedical applications.
Enquiries from prospective PhD students are welcome.
Publications
Journals
Łuksza M, Sethna ZM, Rojas LA, et al., 2022, Neoantigen quality predicts immunoediting in survivors of pancreatic cancer., Nature, Vol:606, ISSN:0028-0836
Bravi B, 2021, il sistema immunitario attraverso la lente dell'inferenza statistica, Ithaca: Viaggio Nella Scienza, Vol:18, ISSN:2282-8079
Bravi B, Balachandran VP, Greenbaum BD, et al., 2021, Probing T-cell response by sequence-based probabilistic modeling, Plos Computational Biology, Vol:17, ISSN:1553-734X, Pages:1-27
Bravi B, Tubiana J, Cocco S, et al., 2021, RBM-MHC: a semi-supervised machine-learning method for sample-specific prediction of antigen presentation by HLA-I alleles, Cell Systems, Vol:12, ISSN:2405-4712, Pages:195-202.e9
Bravi B, Rubin KJ, Sollich P, 2020, Systematic model reduction captures the dynamics of extrinsic noise in biochemical subnetworks., Journal of Chemical Physics, Vol:153, ISSN:0021-9606, Pages:1-20