Metabolite quantification software tools | NMR-based metabolomics data analysis
Recent advances in metabolomics have enabled investigation of human diseases at metabolite level, revealing mechanistic and diagnostic information. High-throughput metabolic phenotyping in epidemiological studies has identified several molecular species present in complex biofluids as being associated with disease risk. Metabolomics therefore provides a useful tool in systems biology research. Due to its quantitative nature, nuclear magnetic resonance (NMR) is considered one of the key analytical platforms for metabolomics.
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 with analyze and management of multiple types of spectral and chemical data. KnowItAll Informatics System is an application that integrates toolsets for: spectral search, spectral identification, mixture analysis, multi-technique spectral data management, nuclear magnetic resonance (NMR) prediction, processing and subtraction, quality control analysis, reporting and publishing tools among others.
A probabilistic approach Bayesian Quantification for fully automated database-based identification. BQuant also automated quantification of metabolites in local regions of 1H NMR spectra. It represents the spectra as mixtures of reference profiles from a database, and infers the identities and the abundances of metabolites by Bayesian model selection. BQuant outperforms the available automated alternatives in accuracy for both identification and quantification.
Accounts for signal interferences in complex experimental spectra typically observed in metabolomics studies. AQuA is able to reduce the amount of nuclear magnetic resonance (NMR) spectral data used in the accurate computation of metabolite quantities. It employs one specific signal for the quantification of each metabolite. It simplifies the utilisation of NMR for metabolomics analysis of human plasma.
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