Assembling Disease Networks From Causal Interaction Resources.

ABSTRACT: The development of high-throughput high-content technologies and the increased ease in their application in clinical settings has raised the expectation of an important impact of these technologies on diagnosis and personalized therapy. Patient genomic and expression profiles yield lists of genes that are mutated or whose expression is modulated in specific disease conditions. The challenge remains of extracting from these lists functional information that may help to shed light on the mechanisms that are perturbed in the disease, thus setting a rational framework that may help clinical decisions. Network approaches are playing an increasing role in the organization and interpretation of patients' data. Biological networks are generated by connecting genes or gene products according to exp

SUBMITTER: Cesareni G 

PROVIDER: S-EPMC8226215 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature