Generic backend for protein prediction web servers

Description:

This is a generic web-server framework for protein structure prediction,
supposed to run on the computational node as a backend.
called by WSDL

Author

Nanjiang Shu

System developer at NBIS

Email: nanjiang.shu@scilifelab.se

Reference

Installation

1. Install dependencies for the web server

   • Apache
   • mod_wsgi

2. Install the virtual environments by

   $ bash setup_virtualenv.sh

3. Create the django database db.sqlite3

4. Run

   $ bash init.sh

   to initialize the working folder

5. In the folder proj, create a softlink of the setting script.

   For development version

    $ ln -s dev_settings.py settings.py
   

   For release version

    $ ln -s pro_settings.py settings.py
   

   Note: for the release version, you need to create a file with secret key and stored at /etc/django_pro_secret_key.txt

6. On the computational node. run

   $ virtualenv env --system-site-packages

   to make sure that python can use all other system-wide installed packages

Supported methods

• TOPCONS2
• SCAMPI2-single
• SCAMPI2-MSA
• SubCons (using Docker)
• ProQ3/ProQ3D (using Docker)
• PRODRES

Variables

• variable for the software to be used: name_software