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Results: 1 to 20 of 101

Similar articles for PubMed (Select 24336413)

1.

HAMMER: automated operation of mass frontier to construct in silico mass spectral fragmentation libraries.

Zhou J, Weber RJ, Allwood JW, Mistrik R, Zhu Z, Ji Z, Chen S, Dunn WB, He S, Viant MR.

Bioinformatics. 2014 Feb 15;30(4):581-3. doi: 10.1093/bioinformatics/btt711. Epub 2013 Dec 11.

2.

Automated analysis of filamentous microbial morphology with AnaMorf.

Barry DJ, Williams GA, Chan C.

Biotechnol Prog. 2015 May;31(3):849-52. doi: 10.1002/btpr.2087. Epub 2015 May 6.

PMID:
25864556
3.

Mass spectral similarity for untargeted metabolomics data analysis of complex mixtures.

Garg N, Kapono C, Lim YW, Koyama N, Vermeij MJ, Conrad D, Rohwer F, Dorrestein PC.

Int J Mass Spectrom. 2015 Feb 1;377:719-717.

PMID:
25844058
4.

Bioinformatics: the next frontier of metabolomics.

Johnson CH, Ivanisevic J, Benton HP, Siuzdak G.

Anal Chem. 2015 Jan 6;87(1):147-56. doi: 10.1021/ac5040693. Epub 2014 Nov 20. No abstract available.

PMID:
25389922
5.

LipidBlast templates as flexible tools for creating new in-silico tandem mass spectral libraries.

Kind T, Okazaki Y, Saito K, Fiehn O.

Anal Chem. 2014 Nov 18;86(22):11024-7. doi: 10.1021/ac502511a. Epub 2014 Nov 6.

PMID:
25340521
6.

Stronger findings for metabolomics through Bayesian modeling of multiple peaks and compound correlations.

Suvitaival T, Rogers S, Kaski S.

Bioinformatics. 2014 Sep 1;30(17):i461-7. doi: 10.1093/bioinformatics/btu455.

7.

Solution-based indirect affinity selection mass spectrometry--a general tool for high-throughput screening of pharmaceutical compound libraries.

O'Connell TN, Ramsay J, Rieth SF, Shapiro MJ, Stroh JG.

Anal Chem. 2014 Aug 5;86(15):7413-20. doi: 10.1021/ac500938y. Epub 2014 Jul 23.

PMID:
25033415
8.

Building blocks for automated elucidation of metabolites: natural product-likeness for candidate ranking.

Jayaseelan KV, Steinbeck C.

BMC Bioinformatics. 2014 Jul 5;15:234. doi: 10.1186/1471-2105-15-234.

9.

Mass++: A Visualization and Analysis Tool for Mass Spectrometry.

Tanaka S, Fujita Y, Parry HE, Yoshizawa AC, Morimoto K, Murase M, Yamada Y, Yao J, Utsunomiya SI, Kajihara S, Fukuda M, Ikawa M, Tabata T, Takahashi K, Aoshima K, Nihei Y, Nishioka T, Oda Y, Tanaka K.

J Proteome Res. 2014 Jul 7. [Epub ahead of print]

PMID:
24965016
10.

Computational analyses of spectral trees from electrospray multi-stage mass spectrometry to aid metabolite identification.

Cao M, Fraser K, Rasmussen S.

Metabolites. 2013 Oct 31;3(4):1036-50. doi: 10.3390/metabo3041036.

11.

CASMI-The Small Molecule Identification Process from a Birmingham Perspective.

Allwood JW, Weber RJ, Zhou J, He S, Viant MR, Dunn WB.

Metabolites. 2013 May 21;3(2):397-411. doi: 10.3390/metabo3020397.

12.

Stronger findings from mass spectral data through multi-peak modeling.

Suvitaival T, Rogers S, Kaski S.

BMC Bioinformatics. 2014 Jun 19;15:208. doi: 10.1186/1471-2105-15-208.

13.

RAMClust: a novel feature clustering method enables spectral-matching-based annotation for metabolomics data.

Broeckling CD, Afsar FA, Neumann S, Ben-Hur A, Prenni JE.

Anal Chem. 2014 Jul 15;86(14):6812-7. doi: 10.1021/ac501530d. Epub 2014 Jun 26.

PMID:
24927477
14.

An R package to analyse LC/MS metabolomic data: MAIT (Metabolite Automatic Identification Toolkit).

Fernández-Albert F, Llorach R, Andrés-Lacueva C, Perera A.

Bioinformatics. 2014 Jul 1;30(13):1937-9. doi: 10.1093/bioinformatics/btu136. Epub 2014 Mar 17.

15.

BiPACE 2D--graph-based multiple alignment for comprehensive 2D gas chromatography-mass spectrometry.

Hoffmann N, Wilhelm M, Doebbe A, Niehaus K, Stoye J.

Bioinformatics. 2014 Apr 1;30(7):988-95. doi: 10.1093/bioinformatics/btt738. Epub 2013 Dec 20.

16.

Chemical structure informing statistical hypothesis testing in metabolomics.

Zhu H, Luo M.

Bioinformatics. 2014 Feb 15;30(4):514-22. doi: 10.1093/bioinformatics/btt708. Epub 2013 Dec 5.

17.

In silico enzymatic synthesis of a 400,000 compound biochemical database for nontargeted metabolomics.

Menikarachchi LC, Hill DW, Hamdalla MA, Mandoiu II, Grant DF.

J Chem Inf Model. 2013 Sep 23;53(9):2483-92. doi: 10.1021/ci400368v. Epub 2013 Sep 12.

18.

Predicting network activity from high throughput metabolomics.

Li S, Park Y, Duraisingham S, Strobel FH, Khan N, Soltow QA, Jones DP, Pulendran B.

PLoS Comput Biol. 2013;9(7):e1003123. doi: 10.1371/journal.pcbi.1003123. Epub 2013 Jul 4.

19.
20.

Automatic chemical structure annotation of an LC-MS(n) based metabolic profile from green tea.

Ridder L, van der Hooft JJ, Verhoeven S, de Vos RC, Bino RJ, Vervoort J.

Anal Chem. 2013 Jun 18;85(12):6033-40. doi: 10.1021/ac400861a. Epub 2013 May 31.

PMID:
23662787
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