Implementation Details

  • 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.

  • Resources for miRNA target data:
    The miRNA targets were predicted base on two algorithms with default parameters - miRanda (score >= 140) and TarPmiR (probability >= 0.5).
  • The web application framework:

    Java Server Faces Technology using the PrimeFaces component library.

  • Network visualization and analysis.

    jquery for general purpose scripting.
    sigma.js for network display and interactions.
    igraph: network analysis and layout.

Server hardware

Xeno-miRNet is currently hosted on a Google Cloud Computing Engine with 30G RAM and 8 CPU cores (n1-standard-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.

Contact & Support

The Xeno-miRNet software is developed and maintained in the Xia Lab at McGill University, QC Canada. For bug reports, comments or suggestions, please email to Jeff Xia (jeff.xia at mcgill.ca).

Acknowledgement

McGill NSERC
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