masterliner.blogg.se - Openlierox level decompiler

#Openlierox level decompiler full#
#Openlierox level decompiler software#
#Openlierox level decompiler code#

* Time scale separation analysis this allows definition of fast and slow components of the model, in a time-dependent way.

* Metabolic control analysis (a special form of sensitivity analysis).

This can be done over several different experiments simultaneously, including mixtures of steady-state and time course experiments.

* Parameter estimation using a range of diverse optimization algorithms.

* Optimization of arbitrary components of the model using a range of diverse algorithms.

* Stoichiometric analysis of the reaction network, including mass conservation analysis and elementary flux modes.

Models can be analyzed and modified with a large set of methods: Simulations can be of time courses or steady states.

* Hybrid LSODA/SSA for hybrid simulations with stochastic kinetics and differential equations.

* Hybrid Runge-Kutta/SSA for hybrid simulations with stochastic kinetics and differential equations.

* Adaptive SSA/τ-leap algorithm for faster (approximate) stochastic kinetics.

* τ-leap algorithm for faster (approximate) stochastic kinetics.

* Gibson-Brooke's version of Gillespie's algorithm for exact stochastic kinetics.

* Gillespie's direct method for exact stochastic kinetics.

* LSODAR for ordinary differential equation modeling.

#Openlierox level decompiler software#

The software provides an interface to create parameter scans (sweeps), parameter sampling and repeated simulations - including complex simulation scenarios mixing parameter samples with scans and repeats of simulations (or other analyses). Simulation can be performed either with stochastic kinetics or with differential equations, and the software easily allows switching between them.

#Openlierox level decompiler code#

Models can also be exported in XPP format, Berkeley Madonna format, and as C code (in addition to MathML and Latex).

#Openlierox level decompiler full#

* the full set of differential equations these can be exported in Latex or MathML formats.ĬOPASI can import and export models in the SBML format (levels 1 to 3).* an arbitrary number of network diagrams (including an SBGN-compliant option).* the GUI interface, with tables for reactions, species, compartments, etc.* The rates of reaction can be picked from a set of predefined kinetic functions (the most common in biochemistry), or arbitrary functions defined by the user.

* Compartments can have variable sizes (ie they can be variables of the model).

* Arbitrary differential equations these have to be added explicitly by the user and can be mapped to species, compartments, or generic variables.* Arbitrary discrete events these can be used to change the model, or just to monitor the progress of simulations.* Unlimited number of species, reactions, and compartments.COPASI automatically converts the reaction network to a set of differential equations or to a system of stochastic reaction events - the user does not have to write down the math explicitly, the software does that. This maps directly to biochemical reaction networks, but can also represent other types of processes (for example, the species could be cell types). Each species is located in a compartment, which is a physical location with a size (volume, area, etc). Models in COPASI are based on reactions that convert a set of species into another set of species. COPASI provides means to visualize data in customizable plots, histograms and animations of network diagrams. COPASI is a software application for simulation and analysis of biochemical networks and their dynamics.ĬOPASI is a stand-alone program that supports models in the SBML standard and can simulate their behavior using ODEs or Gillespie's stochastic simulation algorithm arbitrary discrete events can be included in such simulations.ĬOPASI carries out several analyses of the network and its dynamics and has extensive support for parameter estimation and optimization.