miRGator v2.0 : an integrated system for functional investigation of microRNAs

Abstract

miRGator is an integrated database of microRNA (miRNA)-associated gene expression, target prediction, disease association and genomic annotation, which aims to facilitate functional investigation of miRNAs. The recent version of miRGator v2.0 contains information about (i) human miRNA expression profiles under various experimental conditions, (ii) paired expression profiles of both mRNAs and miRNAs, (iii) gene expression profiles under miRNA-perturbation (e.g. miRNA knockout and overexpression), (iv) known/predicted miRNA targets and (v) miRNA-disease associations. In total, >8000 miRNA expression profiles, ∼300 miRNA-perturbed gene expression profiles and ∼2000 mRNA expression profiles are compiled with manually curated annotations on disease, tissue type and perturbation. By integrating these data sets, a series of novel associations (miRNA–miRNA, miRNA–disease and miRNA–target) is extracted via shared features. For example, differentially expressed genes (DEGs) after miRNA knockout were systematically compared against miRNA targets. Likewise, differentially expressed miRNAs (DEmiRs) were compared with disease-associated miRNAs. Additionally, miRNA expression and disease-phenotype profiles revealed miRNA pairs whose expression was regulated in parallel in various experimental and disease conditions. Complex associations are readily accessible using an interactive network visualization interface. The miRGator v2.0 serves as a reference database to investigate miRNA expression and function (http://miRGator.kobic.re.kr).

ProteoMirExpress: Inferring MicroRNA and Protein-centered Regulatory Networks from High-throughput Proteomic and mRNA Expression Data

“…Moreover, the conditionspecific mRNA-miRNA network integrator (mirConnX) uses transcription factor (TF) binding in the promoter region of miRNAs, as well as mRNA, to construct a transcriptional-posttranscriptional regulatory network (21). In addition, miRNA function can also be annotated by its target genes' enrichments in biological pathways, gene ontology, or diseases (11,(22)(23)(24).…”

Non-coding transcription characterization and annotation

“…[71][72][73][74][75][76][77][78] These databases, which are indexed by NRDR, integrate data sets of regulation (e.g., transcription factor binding sites, or epigenetic markers), expression, target genes and putative regulated networks and pathways. However, there is still a lack of data integrating these transcripts with proteins.…”

A Pathway-Based Classification of Breast Cancer Integrating Data on Differentially Expressed Genes, Copy Number Variations and MicroRNA Target Genes

“…For the identification of miRNA-regulated mRNAs related in breast cancer, we calculated Pearson's correlations for all combinations of miRNA-mRNA pairs over a series of samples in each data set and compiled co-expressed miRNA-mRNA pairs that show significant correlations. (For a description of the association analysis between miRNA-mRNA pairs in detail, please refer to Cho et al, 2011) Incorporation of pathway information A total of 225 control samples, which were used in the calculation of molecular pathway activity, were collected from seven independent data sets (GSE5764, GSE7904, GSE8977, GSE-10780, GSE10810, GSE15043, GSE17907) (Chen et al, 2010;Gu et al, 2009;Karnoub et al, 2007;Pedraza et al, 2010;Richardson et al, 2006;Sircoulomb et al, 2010;Turashvili et al, 2007). 1,340 pathway information were also downloaded from the Pathway Commons database.…”