Coordinator: Daniele Santoni
Description
BioSys is an interdisciplinary research unit designing and applying computational methods to complex biological systems.
Research Activities
BIOLOGICAL NETWORKS
Using graph theory to investigate and extract information in complex biological networks.
BIOLOGICAL PROCESSES
New approaches and problems are studied to identify altered biological processes related to pathologies, environmental damage or drug effects. For this purpose transcriptomic and genomics data are analyzed, through statistics, machine learning and systems biology techniques.
IMMUNOINFORMATICS
Analysis of pathogen and self peptides: distance from self, MHC class I binding, proteasome cleavage, TAP transport, sequence composition entropy and Peptide Hamming Networks to identify potential T-cell epitopes.
MATHEMATICAL MODELING IN SYSTEMS BIOLOGY
Multiscale integrated models of cell metabolism, growth and cycle in yeast, parameter identification of kinetic metabolic models, constraint based analysis of metabolic networks (MFA, FBA, C13-MFA), stochastic modeling (CME) of tumour growth and epidemic diffusion.
OMICS DATA
Analysis of genomics, transcriptomics, metabolomics and proteomics data through the development and application of computational and mathematical approaches.
REGULATION OF GENE EXPRESSION
Analysis of Transcription Factors, chromatin structure, nucleosome occupancy and epigenetics data to investigate and understand the mechanisms underlying altered gene expression in human disease.
VIRUS MUTATION TRAJECTORY
Using information theory to investigate virus evolution and identification of potential clusters of mutation through NGS data.