Computational Biology and Network Biology

Complex biological systems may be represented and mathematically analyzed as computable networks, using graph theory. I am mainly interested in experimental and computational methods for the reconstruction and analysis of protein-protein interaction (PPI) networks (that in a cell form protein interaction networks, PINs), gene regulatory networks (GRNs, DNA-protein interaction networks), signaling networks (signals are transduced within cells or in between cells and thus form complex signaling networks) and metabolic networks.


      Data Integration, Reconstruction, Quantitative Modeling and Analysis of Cellular Signaling Networks of the Immune System

Omics data and computational approaches are today providing a key to disentangle the complex architecture of living systems. The integration and analysis of data of different nature allows to extract meaningful representations of signaling pathways and protein interactions networks, helpful in achieving an increased understanding of such intricate biochemical processes.


      Theoretical Immunology

The network paradigm, an application of graph theory to biology, has proven to be a powerful approach to gaining insights into biological complexity, and has catalyzed the advancement of systems biology. In this perspective and focusing on the immune system, there is a pressing need to a more comprehensive view, and to go beyond the concept of network. The concept of degeneracy, one of the most prominent characteristic of biological complexity, is defined as the ability of structurally different elements to perform the same function. Degeneracy is highly intertwined with another recently-proposed organizational principle, i.e. 'bow tie architecture'. The simultaneous consideration of concepts such as degeneracy, bow tie architecture and network results in a powerful new interpretative tool that takes into account the constructive role of noise and is able to grasp the major characteristics of biological complexity, i.e. the capacity to turn an apparently chaotic and highly dynamic set of signals into functional information.


      Tools For Data Integration

Pathintegrator [ Cytoscape plugin ] - Pathintegrator searches for, and integrates in a single network pathways in which a given gene or protein is involved.





      Open Multiscale Systems Medicine OpenMultiMed COST Action 15120


      KEPAMOD - Knowledge exchange in processing and analysis of multi-omic data 2012-2015, P.I.


      MISSION-T2D - Multiscale Immune System Simulator for the ONset of Type 2 Diabetes integrating genetic, metabolic and nutritional data 2013-2016, P.I.


      INTEROMICS - Development of an integrated platform for the application of "omic" sciences to biomarker definition and theranostic, predictive and diagnostic profiles 2012-2014


      GEHA – Genetics of Healthy Aging 2004-2010, researcher


      BioPharmaNet – Network Labs for Life Sciences 2008-2010, researcher