Computer modelling has become an integral tool in the analysis and understanding of the reaction networks that underlie cellular processes. PySCeS, first released in 2003, is extremely flexible, user-extensible, open source, software actively used and developed by a community of researchers and developers. Features Simulate your time courses with solvers like LSODA and CVODE. Efficiently determine steady states using a selection of non-linear, root-finding algorithms (e.g. HYBRD, NLEQ2). Use Metabolic Control Analysis (MCA) to investigate control and regulation of cellular systems (elasticities, flux- and concentration-control and response coefficients). Auto-generate the stoichiometric matrix and perform structural analysis, determine nullspaces and reduced stoichiometric and MCA matrices. Investigate systems which exhibit multiple (stable and unstable) steady-state solutions using a PITCON-based bifurcation analysis module. Define models with a human-readable Model Description Language. Use the full power of Python available to test, build and share your modelling experiments. User-friendly methods for generating and 1-, 2- and n-dimensional parameter scans. Distributed parameter scanning with the ParScanner module within the ipyparallel framework. Visualise results of simulations with flexible Matplotlib and Gnuplot interfaces. PySCeS supports open community standards for model exchange (SBML) and archiving (SEDML, OMEX). Installation PyPI pip install pysces Anaconda.org conda install -c conda-forge -c pysces pysces Getting help We currently encourage users to ask questions and request support using a GitHub issue. General information on PySCeS can be found on the website and extensive documentation on installing, configuring and using PySCeS is available on pyscesdocs.readthedocs.io.

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