The research interest of our group lies at the interface between statistical physics, computer science, information theory and computational biology. Its main themes include equilibrium and out-of-equilibrium phenomena in disordered systems, statistical physics of inverse problems, statistical inference and combinatorial optimization, probabilistic message-passing algorithms, stochastic processes, randomized algorithms, graphical games and coding. Currently we are focused on the understanding and the development of probabilistic message passing algorithms (MPA) of different degrees of complexity.
MPA have been developed in the last few years in the context of Statistical Physics of Constraint Satisfaction Problems where they have proven to be effective in dealing with optimization problems over random structures. In many cases, MPA are able to explore efficiently the space of solutions in parallel, maintaining a fully distributed updating scheme that keeps the computational effort at a low level.
A main field of applications of our techniques consists in large scale inverse problems in Computational Biology.
The members of the group cover a wide spectrum of competence, from statistical physics, to computer science and information theory, to computational biology and computational neuroscience.
The research activity in computational biology is supported by Microsoft External Research Initiative.
Mon, 02/02/2015 (All day) - Fri, 06/02/2015 (All day)
Advances in experimental technologies deeply transformed the world of biological research over the last decade. Remarkable examples of data obtained using such technologies include - but are not limited to - thousands of fully sequenced genomes, genome-wide measurements of gene expression or methylation profiles and experimental determination of genome-scale protein-protein interaction networks. Due to the nature of the problems involved, the progress of experimental and bioinformatical techniques has been often uneven: the amount of data requires in many cases the solution of hard problems which are intractable by conventional computational tools. The central themes of the conference will be the computational and information-theoretic aspects of network biology with the aim of presenting the state of the art in many research fields that in the last years have seen a relevant burst of activity.
Nowadays, in order to make innovations in an advanced scientific and technological context - new materials, nanoscience, system biology, neuroscience, computation, network engineering, web economy, financial markets modeling - it is mandatory to master the most advanced concepts and methodologies for complex systems. This is why we have set up a master program, based in prestigious sites in Italy and France, which aims to offer the best techniques needed to attack interdisciplinary problems.
The aim of the international master in Physics of Complex Systems is to shape professionals and/or potential researchers able to jointly apply knowledge and methodologies from modern physics, applied mathematics, information engineering and computational biology to the analysis, modeling and simulation of complex systems.
A Conference on Statistical physics of complexity, optimization, and systems biology