Infernet
THE PROJECT:
The goals of INFERNET rely on the transfer of ideas from statistical inference, optimization techniques and high- performance computing methods into the world of quantitative biology. The consortium will provide the optimal environment to nurture a generation of researchers that aims at driving research at the forefront of these developments. The perimeter of each individual research activity will be delimited by: (a) the research themes characterized by the toolbox and methods developed and shared within INFERNET, (b) the choice of the application domains. Each individual research project will be a puzzle piece of the wider research project, as well as tailored to suit each researcher needs of scientific and professional development.

Two main research themes will be covered by the consortium:

INFERENCE OF INTERACTION NETWORKS FROM DATA
A major challenge in computational biology is to use data to unveil the interrelations between biological processes and the molecules contributing to them in terms of regulatory networks. The analysis will produce topological description (who is directly coupled with whom?), and quantitative functional description (how things interact?).

ANALYSIS OF STATIC AND DYNAMICAL PROCESSES ON NETWORKS
INFERNET aim at developing distributed algorithmic techniques for a few key inference problems in molecular systems biology such as large scale models of proliferative metabolism, and large scale models of post-transcriptional microRNA mediated regulation.