COMBINE 2016 Day 3: SigNetSim, A web-based framework for designing kinetic models of molecular signaling networks



Vincent Noel

He was asked to develop a web tool which would be easy for biologists and students, but which could use a parallel simulated annealing algorithm and perform model reduction. He used Python to write the core library and the web interface, with some parts of the library in C. In this software, an SBML model is read in and a symbolic math model is built. It is compatible with SBML up to version of L3V1. The integration is performed using C-generated code, which can be executed in parallel. To perform integration for systems of ODEs or DAEs, the software uses the Sundials library. To perform model fitting, the software uses simulated annealing. It also has some compatibility with Jupyter, mainly to allow the symbolic math model to be able to be worked with directly.

SigNetSim’s web interface uses the Django framework with the Bootstrap front end. There is also a simple DB backend for storing experimental data for these models. The library and web interface will be on github, and the paper should be submitted in the next few months.

Please note that this post is merely my notes on the presentation. I may have made mistakes: these notes are not guaranteed to be correct. Unless explicitly stated, they represent neither my opinions nor the opinions of my employers. Any errors you can assume to be mine and not the speaker’s. I’m happy to correct any errors you may spot – just let me know!


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