Research
Interests, publications
Research interests
I am interested in uncovering the physical principles that govern the phenomena of life. To this aim, a deep dive into the concept of biological function is essential. I do this by building upon ideas from statistical mechanics and information theory.
Theoretical neuroscience
Development and plasticity of nervous systems. Representation and analysis of sensory information.
Statistical inference
Maximum entropy inference: Direct Coupling Analysis (DCA) and Exponential Random Graph (ERG) models.
Evolution
Statistical genetics (multilocus evolution) and fitness landscape theory. Genetic algorithms.
Publications
Journal articles
6. V Dichio, F De Vico Fallani (2023). Exploration-exploitation paradigm for networked biological systems, Phys Rev Lett 132(9), 098402 (Editor's selection) | See also press release [link,link]
5. V Dichio, F De Vico Fallani (2023). Statistical models of complex brain networks: a maximum entropy approach, Rep Prog Phys 86 102601.
4. V Dichio, H Zeng, E Aurell (2023). Statistical genetics in and out of quasi-linkage equilibrium, Rep Prog Phys 86 052601.
3. H Zeng, Y Liu, V Dichio, E Aurell (2022). Temporal epistasis inference from more than 3 500 000 SARS-CoV-2 genomic sequences, Phys Rev E 106, 044409.
2. H zeng, E Mauri, V Dichio, S Cocco, R Monasson, E Aurell (2021). Inferring epistasis from genomic data with comparable mutation and outcrossing rate, J Stat Mech 083501.
1. H Zeng, V Dichio, E Rodriguez Horta, K Thorell, E Aurell (2020). Global analysis of more than 50,000 SARS-CoV-2 genomes reveals epistasis between eight viral genes, Proc Natl Acad Sci 117 (49) 31519-31526
La_Thèse-intro.pdfAn extract. Read the full text here.
PhD thesis
V Dichio (2023). The exploration-exploitation paradigm: a biophysical approach, arxiv 2312.14850.