Inferring the experimental design for accurate gene regulatory network inference.

ABSTRACT:

Motivation

Accurate inference of gene regulatory interactions is of importance for understanding the mechanisms of underlying biological processes. For gene expression data gathered from targeted perturbations, gene regulatory network (GRN) inference methods that use the perturbation design are the top performing methods. However, the connection between the perturbation design and gene expression can be obfuscated due to problems, such as experimental noise or off-target effects, limiting the methods' ability to reconstruct the true GRN.

Results

In this study, we propose an algorithm, IDEMAX, to infer the effective perturbation design from gene expression data in order to eliminate the potential risk of fitting a disconnected perturbation design to gene expression. We applie

SUBMITTER: Secilmis D 

PROVIDER: S-EPMC8545292 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature