We are actively involved in the development of systems biology standards
- – The Systems Biology Markup Language (SBML)
- – The SBML Level 3 Flux Balance Constraints Package: SBML3FBC (Specifications: Version 1)
- – The Simulation Experiment Description Markup Language (SED-ML)
Software and Tools developed and maintained by our group
CBMPy
PySCeS CBMPy is a new platform for constraint based modelling and analysis. It has been designed using principles developed in the PySCeS simulation software project: usability, flexibility and accessibility. Its architecture is both extensible and flexible using data structures that are intuitive to the biologist (metabolites, reactions, compartments) while transparently translating these into the underlying mathematical structures used in advanced analysis (LP’s, MILP’s). PySCeS CBMPy implements popular analyses such as FBA, FVA, element/charge balancing, network analysis and model editing as well as advanced methods developed specifically for the ecosystem modelling: minimal distance methods, flux minimization and input selection.
The CBMPy project source code is currently hosted on SourceForge
To cater for a diverse range of modelling needs PySCeS CBMPy supports user interaction via:
- – interactive console, scripting for advanced use or as a library for software development
- – GUI, for quick access to a visual representation of the model, analysis methods and annotation tools
- – SOAP based web services: using the Mariner framework much high level functionality is exposed for integration into web tools
Download the latest version from SourceForge
F-A-M-E
MEMESA Tools
PySCeS
PySCeS is the Python Simulator of Cellular Systems. For a network of coupled reactions it does a stoichiometric matrix analysis, calculates the time course and steady state, and does a complete control analysis.
The PySCeS project source code is hosted on GitHub and SourceForge and is now ranked on depsy.org:
PySCeS features:
- – A human readable Model Description Language used to define models.
- – The full power of Python available for you to test, build and share your modelling experiments.
- – Follow a models evolution over time with solvers like LSODA. Need a more flexible/powerful solver easily extend PySCeS functionality by using the industry standard CVODE (via PySUNDIALS)
- – PySCeS includes a selection of non-linear root-finding algorithms that can quickly and efficiently be used to calculate steady state solutions (e.g. HYBRD, NLEQ2).
- – Investigate the control and regulation of cellular systems with a completer Metabolic Control Analysis (MCA) module that evaluates elasticities, flux and concentration control coeffcients and response coefficients.
- – A structural analysis module for determination of nullspaces and reduced stoichiometric matrix for models up to the genome scale.
- – A bifurcation analysis module for the study of systems which exhibit multiple (stable and unstable) steady state solutions (PITCON).
- – User friendly methods for generating and 1,2 and n dimension parameter scans.
- – Visualise the results of simulations with a unifed, flexible plotting interface that allows for the use of multiple backends e.g. Matplotlib and/or Gnuplot.
- – SBML import and export capability is provided by an interface module that converts SBML into the PySCeS MDL and models into SBML.
- – User friendly documentation available as docstrings, HTML and PDF.
- – PySCeS is developed as Open Source software distributed under its own BSD style licence.
Download the latest version from SourceForge, PyPi or try “easy_install pysces”
StochPy
StochPy (Stochastic modelling in Python) is a comprehensive and user-friendly tool for simulating stochastic biological processes.
The StochPy project source code is hosted on SourceForge.
StochPy features:
- – Stochastic simulations, delayed stochastic simulations, and stochastic simulation with cell growth and division
- – A human readable Model Description Language used to define models.
- – The full power of Python available for you to test, build and share your modelling experiments (supports both Python 2.6+ and 3.4+).
- – Visualise the results of simulations Matplotlib.
- – SBML import capability is provided by an interface module that converts SBML into the PySCeS MDL.
- – User friendly documentation available as docstrings, HTML and PDF.
- – StochPy is developed as Open Source software distributed under its own BSD style licence.
Download the latest version from SourceForge
Details on selected software can be viewed in the software feature matrix.
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