ArticleJournal of integrative bioinformatics2021
Modular network inference between miRNA-mRNA expression profiles using weighted co-expression network analysis.
Article in Journal of integrative bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Unique circulating miRNAome signatures captured with distinct molecular states in Lynch syndrome and sporadic colorectal cancer.Molecular oncology · 2026Article
- MiRNA target enrichment analysis of co-expression network modules reveals important miRNAs and their roles in breast cancer progression.Journal of integrative bioinformatics · 2024Article
- Gene-network based analysis of human placental trophoblast subtypes identifies critical genes as potential targets of therapeutic drugs.Journal of integrative bioinformatics · 2023Article
- Reprogramming of Fundamental miRNA and Gene Expression during the Barley-Journal of fungi (Basel, Switzerland) · 2022Article
- Special Issue of the 1st International Applied Bioinformatics Conference (iABC'21).Journal of integrative bioinformatics · 2021Article
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Authors and funding
3 authors.
Funding
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Abstract
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.
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