CIV (version: 1.1, released: February 20, 2014)
Cell Image Velocimetry (CIV) is a MATLAB toolbox that combines cell layer segmentation and image velocimetry algorithms to extract and analyze detailed spatiotemporal information for cell migration, as studied by wound healing assays.
CurveletUtils (version: 1.1, released: October 15, 2009)
Matlab source code for a GUI implementing the edge detection method
MorphoGraphX (version: 1.0.1256, released: May 6, 2015)
MorphoGraphX is a free Linux application for the visualization and analysis of 3D biological datasets. Developed by researchers, it is primarily used for the analysis and quantification of 3D live-imaged confocal datasets. The first public release of MorphoGraphX is described in this eLife paper
MosaicSuite (version: 1.0, released: July 1, 2016)
MosaicSuite started with a ParticleTracker plugin described in this paper Now it includes several of the image-processing algorithms for fluorescence microscopy available as plugins for the popular free image processing software ImageJ2 or Fiji.
TScratch (version: 1.0, released: May 18, 2010)
TScratch is a software tool to automatically analyze wound healing assays (scratch assays), available as a stand-alone application for Macintosh and Windows and as a source code.
WCCNT (version: 1.0, released: June 23, 2016)
WCCNT is collection of TCL scripts to analyze/visualize trajectories of CNT (carbon nanotubes) and water in VMD
CUBISM-MPCF (version: 1.0, released: April 2, 2013)
C++ framework for developing uniform grid resolution codes
CubismZ (version: 0.9, released: October 11, 2016)
Lossy wavelet-based and lossless high-performance data compression of 3D scientific data
FTLE2D (version: 1.0, released: May 18, 2012)
Code package for computing 2D FTLE fields with support for OpenCL on GPUs
Glycocalyx Structures (version: 1.0, released: February 17, 2014)
Glycocalyx structures
LeSS (version: 1.0, released: July 3, 2009)
LeSS (Leaping Stochastic Simulation) is a C++ software package for simulating chemical reactions.
MRAG (version: 1.0, released: October 28, 2014)
C++ framework for developing wavelet-adapted grid codes
Parallel Particle Mesh Library (PPM) (version: 1.2_p1, released: November 12, 2010)
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.
PyMLMC (version: 1.0, released: September 27, 2016)
PyMLMC is a highly modular Python Multi-Level Monte Carlo (MLMC) software targeted at launching and managing Uncertainty Quantification campaigns of deterministic HPC simulation software on super-computers and post-processing the results.
SEM++ (version: 1.0, released: August 14, 2014)
SEM++ contains two implementations of an extended version of the subcellular element method: a C++ version for fast prototyping and a LAMMPS plugin for high-performance computing.
uDeviceX (version: 1.0, released: August 25, 2015)
In Silico Lab-On-A-Chip
BASIS (version: 1.1, released: November 3, 2015)
BASIS is a MATLAB package for posterior sampling in parallel, used for Bayesian Uncertainty Quantification and Propagation of complex and computationally demanding physical models.
CMA-ES (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.
OpenOpal (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.
Pi4U (version: 1.0, released: January 1, 2015)
Pi4U is an extensible framework for non-intrusive Bayesian Uncertainty Quantification and Propagation of complex and computationally demanding physical models, that can exploit massively parallel computer architectures
smTMCMC (version: 1.0, released: August 1, 2016)
Langevin Diffusion Transitional Markov Chain Monte Carlo