1. Overview

Bioscrape has three primary features related to modeling, analysis, simulations, and parameter inference:

1. Models can be imported from SBML files and modified using the internal API. Other than changes to species, parameters, and reactions, users can also add delays to reactions and add assignment rules. Bioscrape provides sensitivity analysis tools for these models to determine how sensitive the model is to local changes in parameters.

2. Bioscrape includes fast deterministic and stochastic simulators written in Cython that can be used to simulate the model. These simulators are flexible supporting many different chemical reaction models and are much faster than other packages where the simulation is done in pure Python. Additionally, Bioscrape allows for the simulation of growing and dividing cells via its cell lineage simulators. However, deterministic delayed reactions are not yet supported when simulating cell lineages (stochastic delay reactions are). It is also possible to write your own simulator, propensities, delays, or cell lineage model that easily integrate with Bioscrape.

3. Bioscrape provides a easy-to-use Bayesian parameter inference module that uses the fast simulators underneath as well as existing Markov Chain Monte Carlo (MCMC) libraries to do parameter inference given data. Bayesian inference sampler using Python emcee is built-in with Bioscrape that allows for estimation of parameter distributions from time-series data. Multiple data conditions, multiple initial conditions, time points, and many other common experimental situations are already addressed with helpful bioscrape inference functions. Additionally, a deterministic parameter inference interface using Python LMFit is also built-in.