HOME > news archive > Two new studies published by the Bicocca-IBFM-CNR Research Team use data science techniques to analyze sequencing data of SARS-CoV-2 virus
Two new studies published by the Bicocca-IBFM-CNR Research Team use data science techniques to analyze sequencing data of SARS-CoV-2 virus
Two new studies were published by the Bicocca -Institute of Bioimaging and Molecular Physiology (IBFM-CNR) research team, composed by Alex Graudenzi, IBFM-CNR researcher, by professors Rocco Piazza, Marco Antoniotti, Carlo Gambacorti-Passerini, by research fellows Daniele Ramazzotti, Fabrizio Angaroni and by IBFM-CNR research associate Davide Maspero.
The study published in Patterns introduces an innovative data science approach named VERSO (Viral Evolution ReconStructiOn) for the analysis of sequencing data of viral genomes.
The new approach allows one to identify a high-resolution model of the evolution of a pathogen through the tracing of genomic mutations, allowing one to reconstruct epidemiological links between infected people, i.e., a potential infectious contact between individuals, as well as to intercept possibly hazardous variants before these spread to the population.
The study published in iScience aims at identifying and quantifying the mechanisms responsible for the generation of variants, again starting from the analysis of sequencing data of viral samples.
The study is focused on the analysis of the processes that determine the onset and spread of viral variants, and which derive from the complex combination of mutational processes induced by the interaction between the virus and its host and the dynamics of transmission of the virus among infected individuals. Data science techniques already applied in the study of cancer have proved effective in identifying different "mutational signatures" in different groups of patients.