An approach of gene regulatory network construction using mixed entropy optimizing context-related likelihood mutual information.

ABSTRACT:

Motivation

The question of how to construct gene regulatory networks has long been a focus of biological research. Mutual information can be used to measure nonlinear relationships, and it has been widely used in the construction of gene regulatory networks. However, this method cannot measure indirect regulatory relationships under the influence of multiple genes, which reduces the accuracy of inferring gene regulatory networks.

Approach

This work proposes a method for constructing gene regulatory networks based on mixed entropy optimizing context-related likelihood mutual information (MEOMI). First, two entropy estimators were combined to calculate the mutual information between genes. Then, distribution optimization was performed using a context-related likelihood algorit

SUBMITTER: Lei J 

PROVIDER: S-EPMC9805593 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature