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SPIW is a MATLAB toolbox, for automated processing of scanning probe microscope images. Tools are applicable to all SPM images, but the main focus is on images with atomic or molecular resolution.
SPIW is primarily a MATLAB toolbox with functions designed to be called in a user's own script. SPIW also has a very basic GUI for browsing and exporting images.
For information on SPIW's performance see our publication ( http://dx.doi.org/10.1063/1.4827076 ) in the Review of Scientific...
math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net
CDTB is a MATLAB toolbox which performs Community Detection
...The user can employ the functions from the MATLAB command line; or he can write his own code, incorporating the CDTB functions; or he can use the Graphical User Interface (GUI) which automates the community detection and includes some datavisualization options.
This is the prototype version of software for robust detecting and segmentation of cell nuclei in 3D fluorescence labeled microscopy images. First release coming soon...
Unix-based preparation and analysis toolbox for molecular simulations
...Task specific input and preparation or analysis function, are easy expandable to meet the scientific characteristic of constant changing properties.
Concepts for efficiently storing and analysing large files in conjunction with graphical visualization and numerical data processing are presented in a Manual.
A documented script collection that allows reproducing all simulations and analysis results presented in the Doctoral thesis of the author.
Implematation of robust depth-based inference tools for microarray data (a scale curve, to measure the dispersion of a set of curves, a rank test to decide if two groups of curves come from the same population, and classification techniques).
The Databionics ESOM Tools offer many data mining tasks using Emergent Self-Organizing Maps. Visualization, clustering, and classification of high-dimensional data using databionics principles can be performed interactively or automatically.
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