Search Results for "log analysis tools"

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...

An implementation of the Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method for MATLAB and R. The supplied functionality includes e.g. cross-validation, kernel parameter optimization, model diagnostics and plot tools.

Unix-based preparation and analysis toolbox for Nanomaterials and Room Temperature Ionic Liquids in Bulk and Slab using bash scripts, Gromacs tools and Matlab functions. NaRIBaS provides a framework that decouples user input parameter and terminal based command lines. NaRIBaS does not replace a simulation software and specific analysis tools like Gromacs, but it allows iterative repetition of tasks while changing specific input parameter.

Tools for mass spectrometry, especially for protein mass spectrometry and proteomics: Quantification tools, converters for Applied Biosystems (Q Star and Q Trap), calculation of in-silico fragmentation spectra, converter for Mascot result files

gfit creates an interface between computational models and experimental data and provides tools for their analysis

This is a MATLAB toolbox for the quality control and scoring of EMAP and SGA genetic interaction data. It includes a graphical user interface and some automatic plot-generating tools.

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.