RT Journal Article
SR Electronic
T1 SSI: A Statistical Sensitivity Index for Chemical Reaction Networks in cancer
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2023.01.12.523784
DO 10.1101/2023.01.12.523784
A1 Biddau, Giorgia
A1 Caviglia, Giacomo
A1 Piana, Michele
A1 Sommariva, Sara
YR 2023
UL http://biorxiv.org/content/early/2023/01/15/2023.01.12.523784.abstract
AB Summary At the cellular level, cancer is triggered by mutations of the proteins involved in signalling networks made of hundreds of reacting species. The corresponding mathematical model consists of a large system of non-linear Ordinary Differential Equations for the unknown proteins concentrations depending on a consistently large number of kinetic parameters and initial concentrations. For this model, the present paper considers the problem of assessing the impact of each parameter and initial concentration on the systemâ€™s output. More specifically, we introduced a statistical sensitivity index whose values can be easily computed by means of principal component analysis, and which leads to the partition of the parametersâ€™ and initial concentrationsâ€™ sets into sensible and non-sensible families. This approach allows the identification of those kinetic parameters and initial concentrations that mostly impact the mutation-driven modification of the proteomic profile at equilibrium, and of those pathways in the network that are mostly affected by the presence of mutations in the cancer cell.Competing Interest StatementThe authors have declared no competing interest.