Implementation Details
  • Resources for miRNA-target data:

    The miRNA target gene data were collected from four well-annotated database miRTarBase v8.0, TarBase v8.0 and miRecords . The data for S.mansoni and S.scrofa are predicted by miRanda by default parameters. The miRNA to molecule interaction data were collected from SM2miR and PharmacomiR. The miRNA to disease interaction data were collected from HMDD 3.2, miR2Disease and PhenomiR 2.0 . The miRNA to epigenetic modifier interaction data were collected from EpimiR. The miRNA to ncRNA interaction data were collected from starBase v2.0. The miRNA to TF interaction data were collected from TransmiR v2.0. The variant annotation data for miRNA, miRNA-binding sites and TF-binding sites were collected from ADmiRE, PolymiRTS v3.0 and SNP2TFBS respectively. Also we optimize the data by removing the duplicated records and those miRNAs which proved to be wrong in miRBase v21. The tissue-specific miRNA annotation data were collected from TSmiR and IMOTA. The exosomal miRNA annotation data were collected from ExoCarta. The miRNA set libraries (Function, Disease, Transcription Factor, Cluster) were collected from TAM 2.0.

  • Resources for xeno-miRNA data:

    Xeno-miRNAs detected from deep sequencing were collected from Exo-miRExplorer. Xeno-miRNAs manually collected from literature included dietary sources, parasites exosome-liked vesicles and virus. Predicted xeno-miRNA data were collected from the study by Shu et al. The xeno-miRNA targets were predicted base on two algorithms with default parameters - miRanda (score >= 140) and TarPmiR (probability >= 0.5).

  • R packages used in statistical analysis:
    • edgeR: differential expression analysis for RNAseq data
    • limma: differential expression analysis for microarray or qPCR data;
    • HTqPCR: quantitative real-time PCR data analysis;
  • Network visualization and analysis
    • jquery: general purpose scripting;
    • sigma.js: network display and interactions;
    • igraph: network analysis and layout;
Server hardware

miRNet is currently hosted on a Google Cloud Computing Engine with 64G RAM and 8 CPU cores (n2-highmem-8). The application server is Glassfish 4.0. Please note, the client-side data visualization requires a modern browser that supports HTML5 canvas and JavaScript. miRNet has been tested under Google Chrome (5.0+), Firefox (3.0+), and Internet Explorer (9.0+). The performance of data visualization depends on the user's computer. For best experience, we recommend using the latest version of Google Chrome on a computer with at least 4GB of physical RAM.

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