Permits users to view and analyze processed Nuclear Magnetic Resonance (NMR) data in multiple, canvas windows with correlated crosshairs and rich annotations. NMRViewJ is a graphic application for visualization and analysis of macromolecular NMR software that proposes advanced analysis tools. This tool facilitates assignments of macromolecular NMR spectra and analysis of datasets used in experiments like relaxation and titration analysis.
Analyses advanced time-domain of magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) data. jMRUI can significantly help the user to track the processing history performed on data. The approach offers basic processing tracking and is not suitable for complex data processing and extensive studies. It helps to better organize the processing history and increases the reproducibility and documentability of all spectroscopic processing.
Assists the spectroscopist in making decisions. XEASY permits to support the analysis of nuclear magnetic resonance (NMR) spectra for three-dimensional structure determination of biological macromolecules. It was developed for working with 2D, 3D and 4D NMR data sets. It includes all the functions performed by the precursor program EASY, which was designed for the analysis of 2D NMR spectra.
Allows users to perform data measurement and processing with a focus on Raman, photoluminescence (PL) and cathodoluminescence (CL) spectroscopy. LabSpec intends to furnish a workflow through an experiment, from visualization of the sample and measurement set-up, to interpretation of the data, and final reporting of the results. It supports EasyNav technology and supplies additional modules including multivariate analysis and 3D volume and surface rendering.
A combined chemoinformatic approach for objective and systematic analysis of untargeted 1H NMR-based metabolic profiles in quantitative genetic contexts. The R/Bioconductor mQTL.NMR package was designed to (i) perform a series of preprocessing steps restoring spectral dependency in collinear NMR data sets to reduce the multiple testing burden, (ii) carry out robust and accurate metabotype quantitative trait locus (mQTL) mapping in human cohorts as well as in rodent models, (iii) statistically enhance structural assignment of genetically determined metabolites, and (iv) illustrate results with a series of visualization tools. Built-in flexibility and implementation in the powerful R/Bioconductor framework allow key preprocessing steps such as peak alignment, normalization, or dimensionality reduction to be tailored to specific problems.