Construction of a TF-miRNA-gene feed-forward loop network predicts biomarkers and potential drugs for myasthenia gravis.

ABSTRACT: Myasthenia gravis (MG) is an autoimmune disease and the most common type of neuromuscular disease. Genes and miRNAs associated with MG have been widely studied; however, the molecular mechanisms of transcription factors (TFs) and the relationship among them remain unclear. A TF-miRNA-gene network (TMGN) of MG was constructed by extracting six regulatory pairs (TF-miRNA, miRNA-gene, TF-gene, miRNA-TF, gene-gene and miRNA-miRNA). Then, 3/4/5-node regulatory motifs were detected in the TMGN. Then, the motifs with the highest Z-score, occurring as 3/4/5-node composite feed-forward loops (FFLs), were selected as statistically significant motifs. By merging these motifs together, we constructed a 3/4/5-node composite FFL motif-specific subnetwork (CFMSN). Then, pathway and GO enrichment analyses

SUBMITTER: Bo C 

PROVIDER: S-EPMC7843995 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature