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File Date Author Commit
 Doc 2017-09-03 Ryan Gutenkunst Ryan Gutenkunst [df35a8] Bug fix for developer documentation
 Example 2017-09-07 Keeyan Keeyan [a0b474] Fixed optimization routine passing iterations p...
 SloppyCell 2017-09-07 Keeyan Keeyan [ef8996] Changed backslash to forward slash and sleep be...
 ddaskr 2017-06-08 Ryan Gutenkunst Ryan Gutenkunst [16e2de] Add history info for f2c'd daskr code into README.
 temp 2017-08-14 Keeyan Keeyan [55e2ee] Re-added temp foler
 test 2017-08-03 Ryan Gutenkunst Ryan Gutenkunst [64aa30] Reorganize package to match standard distutils ...
 .gitignore 2017-08-03 Ryan Gutenkunst Ryan Gutenkunst [64aa30] Reorganize package to match standard distutils ...
 LICENSE.txt 2017-08-03 Ryan Gutenkunst Ryan Gutenkunst [b04d05] Add copy of BSD license
 MANIFEST.in 2017-08-03 Ryan Gutenkunst Ryan Gutenkunst [64aa30] Reorganize package to match standard distutils ...
 README.rst 2017-08-04 Ryan Gutenkunst Ryan Gutenkunst [b35e8b] Add README and setup for PyPI submission
 make_htdocs.py 2007-10-02 Ryan Gutenkunst Ryan Gutenkunst [f0ebb4] Formattting changes
 setup.py 2017-08-04 Ryan Gutenkunst Ryan Gutenkunst [b35e8b] Add README and setup for PyPI submission

Read Me

SloppyCell

SloppyCell is a software environment for simulation and analysis of biomolecular networks. A particular strength of SloppyCell is estimating parameters by fitting experimental data and then calculating the resulting uncertainties on parameter values and model predictions.

SloppyCell was initially developed in the lab of Jim Sethna.

Features

  • 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 uncertainties associated with optimal fits