Andrea Pagnani

Scientific Board and Main Proponent - Statistical physics, combinatorial optimization, bioinformatics, biological modeling, statistical inference

His research interests are: statistical physics of disordered systems, combinatorial optimization algorithms, and statistical inference and computational biology (structural predictions of intra/inter protein interactions from multi­species sequence alignment, statistical modeling of competing, endogenous mRNA, inference of signaling pathways, inference of regulatory networks from “omic”­ data, algorithms for metabolic networks). He co-authrored more than 60 peer reviewed papers. His semina work on the inference of structural properties in proteins from co-evolutionary sequence data has been chosen by the Faculty of 1000 (f1000.com) as exceptional publication in 2011, and by the IEEE CS 2022 technical report of 2014, as among the most relevant challenges in contemporary computational biology and bioinformatics.