Inferring causality in biological oscillators.

ABSTRACT:

Motivation

Fundamental to biological study is identifying regulatory interactions. The recent surge in time-series data collection in biology provides a unique opportunity to infer regulations computationally. However, when components oscillate, model-free inference methods, while easily implemented, struggle to distinguish periodic synchrony and causality. Alternatively, model-based methods test the reproducibility of time series given a specific model but require inefficient simulations and have limited applicability.

Results

We develop an inference method based on a general model of molecular, neuronal and ecological oscillatory systems that merges the advantages of both model-based and model-free methods, namely accuracy, broad applicability and usability. Our method suc

SUBMITTER: Tyler J 

PROVIDER: S-EPMC8696107 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature