Branch-recombinant Gaussian processes for analysis of perturbations in biological time series.

ABSTRACT:

Motivation

A common class of behaviour encountered in the biological sciences involves branching and recombination. During branching, a statistical process bifurcates resulting in two or more potentially correlated processes that may undergo further branching; the contrary is true during recombination, where two or more statistical processes converge. A key objective is to identify the time of this bifurcation (branch or recombination time) from time series measurements, e.g. by comparing a control time series with perturbed time series. Gaussian processes (GPs) represent an ideal framework for such analysis, allowing for nonlinear regression that includes a rigorous treatment of uncertainty. Currently, however, GP models only exist for two-branch systems. Here, we highlight how ar

SUBMITTER: Penfold CA 

PROVIDER: S-EPMC6129282 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature