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JANet

JANet (Jmol AgeFactDB Network-viewer) is a specialized Jmol-based 3D network viewer for the
visualization of ageing-related network data from AgeFactDB.

 JANet 3D viewer interface screenshot

Features

  • Interactive 3D network visualization (rotate, zoom, etc.)
    • 2D representation
    • Stereo representation (e.g.: side by side, red/cyan)
    • 3D beamer mode (condensed side by side stereo, converted for shutter glasses)
      JANet 3D beamer mode example
  • Ageing-related network data (AgeFactDB)
    • Lifespan observations
    • Ageing factors
    • Augmentation nodes (e.g.: allele types, citations)
  • Augmentation with external domain knowledge
    • Gene Ontology (GO)
    • KEGG Pathways
  • Genes of interest analysis (e.g.: differentially expressed genes)
  • Scripting language
    • Jmol scripting language
    • JANet-specific API

Installation

The viewer can be started directly from the server at http://sysbio.uni-ulm.de/software/janet
or downloaded including all necessary network data for local installation
(http://sysbio.uni-ulm.de/software/janet/janet.zip).

For a local installation there are two options:

  1. Extract the archive somewhere in the file system.
  2. Install a web server locally and extract the archive somewhere below the server root directory.

Option 1:  JANet can be started by opening the file \textit{index.html} from the top level directory in a web browser as a local file. In some browsers, like Safari, this requires to switch off a default restriction for local file usage. The Javascript version of JANet will not work in browsers that prevent loading local binary files using Javascript, like Safari and Opera.

Option 2: JANet can be started by adding the relative directory path of the top-level viewer directory to the server name \textit{localhost} for the local web server and open the web address in a web browser.
  (Example:  http://localhost/tools/janet)

Citing JANet

To cite the network viewer in publications, use:


[submitted, no publication available yet]

Latest News

Our paper "A model of the onset of the Senescence Associated Secretory Phenotype after DNA damage induced Senescence" has been accepted for publishing in PLOS Computational Biology.

Our paper "The influence of multi-class feature selection on the prediction of diagnostic phenotypeshas been accepted for publishing in Neural Processing Letters.