Identifying and quantifying metabolites by scoring peaks of GC-MS data

BMC Bioinformatics

Volumn 15, Issue 1, 2014, Pages

  Aggio, Raphael B M ^a,b   Mayor, Arno ^b   Reade, Sophie ^b   Probert, Chris S J ^b   Ruggiero, Katya ^a  

^a UNIVERSITY OF AUCKLAND   (New Zealand)

^b UNIVERSITY OF LIVERPOOL   (United Kingdom)

Author keywords

Data analysis; GC MS; Identification; Metabolomics

Indexed keywords

BIOMOLECULES; CHROMATOGRAPHY; COMPUTATIONAL METHODS; DATA HANDLING; DATA REDUCTION; DRUG PRODUCTS; GAS CHROMATOGRAPHY; IDENTIFICATION (CONTROL SYSTEMS); INFORMATION ANALYSIS; MAMMALS; MASS SPECTROMETRY; THROUGHPUT; VOLATILE ORGANIC COMPOUNDS;

COMPUTATIONAL TOOLS; GAS CHROMATOGRAPHY-MASS SPECTROMETRIES (GC-MS); GC-MS; HIGH-THROUGHPUT DATA; MASS SPECTRAL LIBRARIES; METABOLOME ANALYSIS; METABOLOMICS; VOLATILE ORGANIC COMPOUND (VOC);

METABOLITES;

MUS;

VOLATILE ORGANIC COMPOUND;

ALGORITHM; ANIMAL; C57BL MOUSE; CHEMISTRY; COMPUTER PROGRAM; FECES; FEMALE; MALE; MASS FRAGMENTOGRAPHY; METABOLOME; METABOLOMICS; MOUSE; PROCEDURES; STANDARD;

ALGORITHMS; ANIMALS; FECES; FEMALE; GAS CHROMATOGRAPHY-MASS SPECTROMETRY; MALE; METABOLOME; METABOLOMICS; MICE; MICE, INBRED C57BL; REFERENCE STANDARDS; SOFTWARE; VOLATILE ORGANIC COMPOUNDS;

EID: 84923866676     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-014-0374-2     Document Type: Article

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