SloppyCell is a software environment for simulation and analysis of biomolecular networks.
SloppyCell was developed by Ryan Gutenkunst while in the groups of Jim Sethna and Chris Myers at Cornell University.
Examples of models developed in SloppyCell can be found at Jim Sethna's Gene Dynamics page.
- support for much of the Systems Biology Markup Language (SBML) level 2 version 3
- deterministic and stochastic dynamical simulations
- sensitivity analysis without finite-difference derviatives
- optimization methods to fit parameters to experimental data
- simulation of multiple related networks sharing common parameters
- stochastic Bayesian analysis of parameter space to estimate error bars
associated with optimal fits
To install SloppyCell, download the current snapshot from the git repository.
If you use SloppyCell for published work, please include these references:
Christopher R. Myers, Ryan N. Gutenkunst, James P. Sethna
"Python unleashed on systems biology"
Computing in Science and Engineering 9:34 (2007); arXiv:0704.3259
Ryan N. Gutenkunst, Jordan C. Atlas, Fergal P. Casey, Brian C. Daniels, Robert S. Kuczenski, Joshua J. Waterfall, Chris R. Myers, and James P. Sethna.
SloppyCell. http://sloppycell.sourceforge.net/ (2007)