BATMAN—an R package for the automated quantification of metabolites from nuclear magnetic resonance spectra using a Bayesian model | Zendy

Jie Hao | Zendy; William J. Astle | Zendy; Maria De Iorio | Zendy; Timothy M. D. Ebbels | Zendy

Open Access

BATMAN—an R package for the automated quantification of metabolites from nuclear magnetic resonance spectra using a Bayesian model

Author(s) -

Jie Hao,

William J. Astle,

Maria De Iorio,

Timothy M. D. Ebbels

Publication year - 2012

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bts308

Subject(s) - bayesian probability , deconvolution , markov chain monte carlo , computer science , spectral line , algorithm , monte carlo method , biological system , nmr spectra database , artificial intelligence , nuclear magnetic resonance , pattern recognition (psychology) , mathematics , statistics , physics , biology , astronomy

Nuclear Magnetic Resonance (NMR) spectra are widely used in metabolomics to obtain metabolite profiles in complex biological mixtures. Common methods used to assign and estimate concentrations of metabolites involve either an expert manual peak fitting or extra pre-processing steps, such as peak alignment and binning. Peak fitting is very time consuming and is subject to human error. Conversely, alignment and binning can introduce artefacts and limit immediate biological interpretation of models.

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