diff options
author | Pedro Mendes <pedro@gepasi.org> | 2016-11-30 20:51:14 +0000 |
---|---|---|
committer | Willy Sudiarto Raharjo <willysr@slackbuilds.org> | 2016-12-03 07:17:45 +0700 |
commit | 004c02b09eddc21957004a908251de2e9926eaa4 (patch) | |
tree | 7f77dbdb218fe997151861c715b3eea9da745710 /academic/copasi/README | |
parent | d20e4d268ae7a2f370b7e80e3d4f70e0085a0921 (diff) |
academic/copasi: Updated for version 4.18.136.
Signed-off-by: David Spencer <idlemoor@slackbuilds.org>
Diffstat (limited to 'academic/copasi/README')
-rw-r--r-- | academic/copasi/README | 18 |
1 files changed, 9 insertions, 9 deletions
diff --git a/academic/copasi/README b/academic/copasi/README index d8e33bc6bcf3..9039958d6de7 100644 --- a/academic/copasi/README +++ b/academic/copasi/README @@ -1,16 +1,16 @@ COPASI is a package for modeling and simulation of biochemical networks, popular in the field of systems biology. -COPASI is a stand-alone program that simulates models of biochemical -networks using ODE solvers or Gillespie's stochastic simulation -algorithm. COPASI is compatible with models in SBML format. It also -performs several analyses, such as steady state, stability, parameter -sensitivity, elementary modes, Lyapunov exponents, optimization, and -parameter estimation. Data can be visualized in plots, histograms and -animations of network diagrams. COPASI's GUI is based on QT, but a -command line version is also included that allows for processing +COPASI is a stand-alone program that simulates models of biochemical +networks using ODE solvers or Gillespie's stochastic simulation +algorithm. COPASI is compatible with models in SBML format. It also +performs several analyses, such as steady state, stability, parameter +sensitivity, elementary modes, Lyapunov exponents, optimization, and +parameter estimation. Data can be visualized in plots, histograms and +animations of network diagrams. COPASI's GUI is based on QT, but a +command line version is also included that allows for processing computations in batch mode. COPASI is a collaboration between research groups at the Biocomplexity Institute at Virginia Tech, University of Heidelberg, University of -Connecticut, University of Manchester, and previously the EML-Research. +Connecticut, University of Manchester and previously the EML-Research. |