Search Results for "spectral"

STRIKER is a tool for correcting spectra with missing or incorrect adduct annotations. It also enables efficient construction of an HMDB-based spectral library and extraction of sublibraries from large spectral libraries.

...Organic molecules, proteins, RNA, DNA, sugars, and other biomolecules are all supported. It supports exponential curve fitting for the calculation of the R1 and R2 relaxation rates, calculation of the NOE, reduced spectral density mapping, the Lipari and Szabo model-free analysis, study of domain motions via the N-state model and frame order dynamics theories using anisotropic NMR parameters such as RDCs and PCSs, the investigation of stereochemistry in dynamic ensembles, and the analysis of relaxation dispersion data.

SWATH-Auto System Analyzer Tool, SASA Tool, is a novel SWATH platform for non-targeted metabolomics data analysis with an accurate mass spectral library for metabolite identification using SWATH acquisition mode.

TI2BioP allows mainly the calculation of topological indices (spectral moments) derived from inferred and artificial 2D structures of DNA, RNA and proteins being possible to carry out a structure-function correlation irrespective of sequence alignments. TI2BioP version 3.0 is a python platform with a graphical interface designed for Windows, Linux and Mac OS.

...These challenges are similar but not identical to the challenges arising in the analysis of metagenomic samples and require specific solutions. pipasic (peptide intensity-weighted proteome abundance similarity correction) is a tool which corrects identification and spectral counting based quantification results using peptide similarity estimation and expression level weighting within a non-negative lasso framework. pipasic has distinct advantages over approaches only regarding unique peptides or aggregating results to the lowest common ancestor.

Tandem mass spectral peptide identification and validation software, similar to X!Tandem, OMSSA, MyriMatch. Suitable for single hosts through large clusters. Written in Python for simplicity, with performance-critical sections in C++.

Tools to perform metabolic control analyses on biochemical network models in SBML format. Allows computation of first and second order response coefficients, elasticities, first order control coefficients and first order spectral response coefficients.