Protocol to use TopNet for gene regulatory network modeling using gene expression data from perturbation experiments

STAR Protoc. 2022 Dec 16;3(4):101737. doi: 10.1016/j.xpro.2022.101737. Epub 2022 Sep 30.

Abstract

Inference of gene regulatory networks from gene perturbation experiments is the most reliable approach for investigating interdependence between genes. Here, we describe the initial gene perturbations, expression measurements, and preparation steps, followed by network modeling using TopNet. Summarization and visualization of the estimated networks and optional genetic testing of dependencies revealed by the network model are demonstrated. While developed for gene perturbation experiments, TopNet models data in which nodes are both perturbed and measured. For complete details on the use and execution of this protocol, please refer to McMurray et al. (2021).

Keywords: Bioinformatics; Cancer; Cell Biology; Cell culture; Gene Expression; Genetics; Molecular Biology; Systems biology.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Gene Expression
  • Gene Regulatory Networks*