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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

417 related items for PubMed ID: 19301908

  • 41. IP4M: an integrated platform for mass spectrometry-based metabolomics data mining.
    Liang D, Liu Q, Zhou K, Jia W, Xie G, Chen T.
    BMC Bioinformatics; 2020 Oct 07; 21(1):444. PubMed ID: 33028191
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  • 42. Automated procedure for candidate compound selection in GC-MS metabolomics based on prediction of Kovats retention index.
    Mihaleva VV, Verhoeven HA, de Vos RC, Hall RD, van Ham RC.
    Bioinformatics; 2009 Mar 15; 25(6):787-94. PubMed ID: 19176550
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  • 43. Comparative evaluation of eight software programs for alignment of gas chromatography-mass spectrometry chromatograms in metabolomics experiments.
    Niu W, Knight E, Xia Q, McGarvey BD.
    J Chromatogr A; 2014 Dec 29; 1374():199-206. PubMed ID: 25435458
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  • 46. Metabonomic study of ochratoxin a toxicity in rats after repeated administration: phenotypic anchoring enhances the ability for biomarker discovery.
    Sieber M, Wagner S, Rached E, Amberg A, Mally A, Dekant W.
    Chem Res Toxicol; 2009 Jul 29; 22(7):1221-31. PubMed ID: 19610676
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  • 47. Classification of peptide mass fingerprint data by novel no-regret boosting method.
    Gambin A, Szczurek E, Dutkowski J, Bakun M, Dadlez M.
    Comput Biol Med; 2009 May 29; 39(5):460-73. PubMed ID: 19386298
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  • 48. Preprocessing of raw metabonomic data.
    Vettukattil R.
    Methods Mol Biol; 2015 May 29; 1277():123-36. PubMed ID: 25677151
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  • 49. High-throughput quantitative metabolomics: workflow for cultivation, quenching, and analysis of yeast in a multiwell format.
    Ewald JC, Heux S, Zamboni N.
    Anal Chem; 2009 May 01; 81(9):3623-9. PubMed ID: 19320491
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  • 51. From numbers to a biological sense: How the strategy chosen for metabolomics data treatment may affect final results. A practical example based on urine fingerprints obtained by LC-MS.
    Godzien J, Ciborowski M, Angulo S, Barbas C.
    Electrophoresis; 2013 Oct 01; 34(19):2812-26. PubMed ID: 23775708
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  • 53. Combining peak- and chromatogram-based retention time alignment algorithms for multiple chromatography-mass spectrometry datasets.
    Hoffmann N, Keck M, Neuweger H, Wilhelm M, Högy P, Niehaus K, Stoye J.
    BMC Bioinformatics; 2012 Aug 27; 13():214. PubMed ID: 22920415
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  • 54. Compensation for systematic cross-contribution improves normalization of mass spectrometry based metabolomics data.
    Redestig H, Fukushima A, Stenlund H, Moritz T, Arita M, Saito K, Kusano M.
    Anal Chem; 2009 Oct 01; 81(19):7974-80. PubMed ID: 19743813
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  • 55. MRMkit: Automated Data Processing for Large-Scale Targeted Metabolomics Analysis.
    Teo G, Chew WS, Burla BJ, Herr D, Tai ES, Wenk MR, Torta F, Choi H.
    Anal Chem; 2020 Oct 20; 92(20):13677-13682. PubMed ID: 32930575
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  • 59. QPMASS: A parallel peak alignment and quantification software for the analysis of large-scale gas chromatography-mass spectrometry (GC-MS)-based metabolomics datasets.
    Duan L, Ma A, Meng X, Shen GA, Qi X.
    J Chromatogr A; 2020 Jun 07; 1620():460999. PubMed ID: 32151418
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