Open AccesspJRES Binning Algorithm (JBA): a new method to facilitate the recovery of metabolic information from pJRES 1H NMR spectra
Author(s) -
Andrea RodriguezMartinez,
Rafael Ayala,
Joram M. Posma,
Nikita E. Harvey,
Beatriz Jiménez,
Kazuhiro Sonomura,
Taka-Aki Sato,
Fumihiko Matsuda,
Pierre Zalloua,
Dominique Gauguier,
Jeremy K. Nicholson,
MarcEmmanuel Dumas
Publication year - 2018
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/bty837
Subject(s) - bioconductor , bottleneck , algorithm , computer science , curse of dimensionality , multivariate statistics , proton nmr , key (lock) , data mining , chemistry , artificial intelligence , nuclear magnetic resonance , physics , machine learning , biochemistry , computer security , gene , embedded system
Data processing is a key bottleneck for 1H NMR-based metabolic profiling of complex biological mixtures, such as biofluids. These spectra typically contain several thousands of signals, corresponding to possibly few hundreds of metabolites. A number of binning-based methods have been proposed to reduce the dimensionality of 1 D 1H NMR datasets, including statistical recoupling of variables (SRV). Here, we introduce a new binning method, named JBA ("pJRES Binning Algorithm"), which aims to extend the applicability of SRV to pJRES spectra.
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