METLIN - A metabolite mass spectral database

被引：1721

作者：

Smith, CA ^{[1
]}

O'Maille, G ^{[1
]}

Want, EJ ^{[1
]}

Qin, C ^{[1
]}

Trauger, SA ^{[1
]}

Brandon, TR ^{[1
]}

Custodio, DE ^{[1
]}

Abagyan, R ^{[1
]}

Siuzdak, G ^{[1
]}

机构：

[1] Scripps Res Inst, Ctr Mass Spectrometry, La Jolla, CA 92037 USA

来源：

THERAPEUTIC DRUG MONITORING | 2005年 / 27卷 / 06期

关键词：

METLIN; database; metabolites; LC/MS; FTMS; MS/MS;

D O I：

10.1097/01.ftd.0000179845.53213.39

中图分类号：

R446 [实验室诊断]; R-33 [实验医学、医学实验];

学科分类号：

1001 ;

摘要：

Endogenous metabolites have gained increasing interest over the past 5 years largely for their implications in diagnostic and pharmaceutical biomarker discovery. METLIN (http://metlin. scripps.edu), a freely accessible web-based data repository, has been developed to assist in a broad array of metabolite research and to facilitate metabolite identification through mass analysis. METLIN includes an annotated list of known metabolite structural information that is easily cross-correlated with its catalogue of high-resolution Fourier transform mass spectrometry (FTMS) spectra, tandem mass spectrometry (MS/MS) spectra, and LC/MS data.

引用

页码：747 / 751

页数：5

共 24 条

[1] Integration of knowledge-based metabolic predictions with liquid chromatography data-dependent tandem mass spectrometry for drug metabolism studies: Application to studies on the biotransformation of Indinavir [J].

Anari, MR ;

Sanchez, RI ;

Bakhtiar, R ;

Franklin, RB ;

Baillie, TA .

ANALYTICAL CHEMISTRY, 2004, 76 (03) :823-832

[2] A universal denoising and peak picking algorithm for LC-MS based on matched filtration in the chromatographic time domain [J].

Andreev, VP ;

Rejtar, T ;

Chen, HS ;

Moskovets, EV ;

Ivanov, AR ;

Karger, BL .

ANALYTICAL CHEMISTRY, 2003, 75 (22) :6314-6326

[3] NMR-based metabonomic toxicity classification: hierarchical cluster analysis and k-nearest-neighbour approaches [J].

Beckonert, O ;

Bollard, ME ;

Ebbels, TMD ;

Keun, HC ;

Antti, H ;

Holmes, E ;

Lindon, JC ;

Nicholson, JK .

ANALYTICA CHIMICA ACTA, 2003, 490 (1-2) :3-15

[4] Metabolomics: quantification of intracellular metabolite dynamics [J].

Buchholz, A ;

Hurlebaus, J ;

Wandrey, C ;

Takors, R .

BIOMOLECULAR ENGINEERING, 2002, 19 (01) :5-15

[5] Mass spectrometry in the clinical laboratory [J].

Chace, DH .

CHEMICAL REVIEWS, 2001, 101 (02) :445-477

[6] Role of accurate mass measurement (±10 ppm) in protein identification strategies employing MS or MS MS and database searching [J].

Clauser, KR ;

Baker, P ;

Burlingame, AL .

ANALYTICAL CHEMISTRY, 1999, 71 (14) :2871-2882

[7] Toxicity classification from metabonomic data using a density superposition approach: 'CLOUDS' [J].

Ebbels, T ;

Keun, H ;

Beckonert, O ;

Antti, H ;

Bollard, M ;

Holmes, E ;

Lindon, J ;

Nicholson, J .

ANALYTICA CHIMICA ACTA, 2003, 490 (1-2) :109-122

[8] Computational lipidomics: A multiplexed analysis of dynamic changes in membrane lipid composition during signal transduction [J].

Forrester, JS ;

Milne, SB ;

Ivanova, PT ;

Brown, HA .

MOLECULAR PHARMACOLOGY, 2004, 65 (04) :813-821

[9] A methodology for automated comparative analysis of metabolite profiling data [J].

Frenzel, T ;

Miller, A ;

Engel, KH .

EUROPEAN FOOD RESEARCH AND TECHNOLOGY, 2003, 216 (04) :335-342

[10] The molecular biology database collection: 2004 update [J].

Galperin, MY .

NUCLEIC ACIDS RESEARCH, 2004, 32 :D3-D22

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