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Co-expression networks in predicting transcriptional gene regulation

AbuQamar, S.F., El-Tarabily, K.A. and Sham, A. (2021) Co-expression networks in predicting transcriptional gene regulation. In: Mukhtar, S., (ed.) Modeling Transcriptional Regulation. Humana Press, pp. 1-11.

Link to Published Version: https://doi.org/10.1007/978-1-0716-1534-8_1
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Abstract

Recent progress in transcriptomics and co-expression networks have enabled us to predict the inference of the biological functions of genes with the associated environmental stress. Microarrays and RNA sequencing (RNA-seq) are the most commonly used high-throughput gene expression platforms for detecting differentially expressed genes between two (or more) phenotypes. Gene co-expression networks (GCNs) are a systems biology method for capturing transcriptional patterns and predicting gene interactions into functional and regulatory relationships. Here, we describe the procedures and tools used to construct and analyze GCN and investigate the integration of transcriptional data with GCN to provide reliable information about the underlying biological mechanism.

Item Type: Book Chapter
Murdoch Affiliation(s): Harry Butler Institute
Publisher: Humana Press
Copyright: © 2021 Springer Science+Business Media, LLC, part of Springer Nature
Other Information: Part of the Methods in Molecular Biology book series (MIMB, volume 2328)
URI: http://researchrepository.murdoch.edu.au/id/eprint/61662
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