title: MiRNA-TF-gene network analysis through ranking of biomolecules for multi-informative uterine leiomyoma dataset.
abstract: Gene ranking is an important problem in bioinformatics. Here, we propose a new framework for ranking biomolecules (viz., miRNAs, transcription-factors/TFs and genes) in a multi-informative uterine leiomyoma dataset having both gene expression and methylation data using (statistical) eigenvector centrality based approach. At first, genes that are both differentially expressed and methylated, are identified using Limma statistical test. A network, comprising these genes, corresponding TFs from TRANSFAC and ITFP databases, and targeter miRNAs from miRWalk database, is then built. The biomolecules are then ranked based on eigenvector centrality. Our proposed method provides better average accuracy in hub gene and non-hub gene classifications than other methods. Furthermore, pre-ranked Gene set enrichment analysis is applied on the pathway database as well as GO-term databases of Molecular Signatures Database with providing a pre-ranked gene-list based on different centrality values for comparing among the ranking methods. Finally, top novel potential gene-markers for the uterine leiomyoma are provided.
authors: Machine Intelligence Unit, Indian Statistical Institute, Kolkata 700108, India. Electronic address: sauravmtech2@gmail.com.
authors: Saurav
authors: S
authors: Mallik
authors: Department of Computer Science and Engineering, Jadavpur University, Kolkata 700032, India. Electronic address: umaulik@cse.jdvu.ac.in.
authors: Ujjwal
authors: U
authors: Maulik
mesh_terms: D000818:Animals; D030541:Databases, Genetic; D005260:Female; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D005796:Genes; D007889:Leiomyoma / Q000235:genetics*; D035683:MicroRNAs; D014157:Transcription Factors; D014594:Uterine Neoplasms / Q000235:genetics*
chemical_list: D035683:MicroRNAs; D014157:Transcription Factors
keywords: Differentially expressed and differentially methylated genes; Eigenvector centrality based ranking of biomolecules; Gene-marker; Limma statistical test; TF-miRNA-gene network