Modular network inference between miRNA–mRNA expression profiles using weighted co-expression network analysis

Journal of Integrative Bioinformatics

Wani Nisar¹  Raza Khalid²  Barh Debmalya³ 

[1] Computer Science and Engineering Department, Govt. College of Engineering and Technology Safapora, Ganderbal Kashmir, J&K, India;Department of Computer Science, Jamia Millia Islamia, New Delhi, India;Institute of Integrative Omics and Applied Biotechnology (IIOAB), Nonakuri, Purba Medinipur, WB, India;

关键词: gene expression;    hubs;    mirna;    module detection;    module eigengene networks;    network inference;   

DOI  :  10.1515/jib-2021-0029

来源: DOAJ

【 摘 要 】

Connecting transcriptional and post-transcriptional regulatory networks solves an important puzzle in the elucidation of gene regulatory mechanisms. To decipher the complexity of these connections, we build co-expression network modules for mRNA as well as miRNA expression profiles of breast cancer data. We construct gene and miRNA co-expression modules using the weighted gene co-expression network analysis (WGCNA) method and establish the significance of these modules (Genes/miRNAs) for cancer phenotype. This work also infers an interaction network between the genes of the turquoise module from mRNA expression data and hubs of the turquoise module from miRNA expression data. A pathway enrichment analysis using a miRsystem web tool for miRNA hubs and some of their targets, reveal their enrichment in several important pathways associated with the progression of cancer.

【 授权许可】

Unknown