version: 1.0
released: June 29, 2009
The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for Noisy and Global Optimization is an evolutionary (search) algorithm for difficult optimization problems.
version: 1.1
released: October 15, 2009
Matlab source code for a GUI implementing the edge detection method
version: 1.0
released: July 3, 2009
LeSS (Leaping Stochastic Simulation) is a C++ software package for simulating chemical reactions.
version: 1.0.2
released: June 29, 2009
PPM is a software layer between the Message Passing Interface (MPI) and codes for simulations of physical systems using hybrid particle-mesh methods. The library is based on a unifying formulation for the simulations of discrete and continuous systems using particles.
version: 1.0
released: June 29, 2009
TScratch is a software tool to automatically analyze wound healing assays (scratch assays) available as a stand-alone application on Macintosh (Intel) OS X or PC (Windows) platforms, with or without the Matlab Compiler Runtime (MCR) v7.8 engine.
version: 1.0
released: May 29, 2009
TScratch is a software tool to automatically analyze wound healing assays (scratch assays) available as a stand-alone application on Macintosh (Intel) OS X or PC (Windows) platforms, with or without the Matlab Compiler Runtime (MCR) v7.8 engine.
version: 1.0
released: June 29, 2009
TScratch is a software tool to automatically analyze wound healing assays (scratch assays) available as a stand-alone application on Macintosh (Intel) OS X or PC (Windows) platforms, with or without the Matlab Compiler Runtime (MCR) v7.8 engine.
version: 1.0
released: May 29, 2009
TScratch is a software tool to automatically analyze wound healing assays (scratch assays) available as a stand-alone application on Macintosh (Intel) OS X or PC (Windows) platforms, with or without the Matlab Compiler Runtime (MCR) v7.8 engine.
version: 1.0
released: July 30, 2009
OpenOpal is an Open Source software environment for OPtimization And Learning, providing algorithms for automatic optimization, Design of Experiment, and Machine Learning.