Literature DB >> 17990490

SetupX--a public study design database for metabolomic projects.

Martin Scholz1, Oliver Fiehn.   

Abstract

Metabolomic databases are useless without accurate description of the biological study design and accompanying metadata reporting on the laboratory workflow from sample preparation to data processing. Here we report on the implementation of a database system that enables investigators to detail and set up a biological experiment, and that also steers laboratory workflows by direct access to the data acquisition instrument. SetupX utilizes orthogonal biological parameters such as genotype, organ, and treatment(s) for delineating the dimensions of a study which define the number of classes under investigation. Publicly available taxonomic and ontology repositories are utilized to ensure data integrity and logic consistency of class designs. Class descriptions are subsequently employed to schedule and randomize data acquisitions, and to deploy metabolite annotations carried out by the seamlessly integrated mass spectrometry database, BinBase. Annotated result data files are housed by SetupX for downloads and queries. Currently, 39 users have generated 48 studies, some of which are made public.

Mesh:

Year:  2007        PMID: 17990490

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  72 in total

1.  Skeletal muscle interstitial fluid metabolomics at rest and associated with an exercise bout: application in rats and humans.

Authors:  Jie Zhang; Sudeepa Bhattacharyya; Robert C Hickner; Alan R Light; Christopher J Lambert; Bruce K Gale; Oliver Fiehn; Sean H Adams
Journal:  Am J Physiol Endocrinol Metab       Date:  2018-11-06       Impact factor: 4.310

2.  Loss of caveolin-1 expression in knock-in mouse model of Huntington's disease suppresses pathophysiology in vivo.

Authors:  Eugenia Trushina; Christie A Canaria; Do-Yup Lee; Cynthia T McMurray
Journal:  Hum Mol Genet       Date:  2013-09-10       Impact factor: 6.150

3.  Habitual physical activity and plasma metabolomic patterns distinguish individuals with low vs. high weight loss during controlled energy restriction.

Authors:  Brian D Piccolo; Nancy L Keim; Oliver Fiehn; Sean H Adams; Marta D Van Loan; John W Newman
Journal:  J Nutr       Date:  2015-01-28       Impact factor: 4.798

4.  Pharmacometabolomic signature links simvastatin therapy and insulin resistance.

Authors:  Mona Elbadawi-Sidhu; Rebecca A Baillie; Hongjie Zhu; Yii-Der Ida Chen; Mark O Goodarzi; Jerome I Rotter; Ronald M Krauss; Oliver Fiehn; Rima Kaddurah-Daouk
Journal:  Metabolomics       Date:  2016-12-23       Impact factor: 4.290

Review 5.  Metabolomics: moving to the clinic.

Authors:  Anders Nordström; Rolf Lewensohn
Journal:  J Neuroimmune Pharmacol       Date:  2009-04-28       Impact factor: 4.147

Review 6.  Database resources in metabolomics: an overview.

Authors:  Eden P Go
Journal:  J Neuroimmune Pharmacol       Date:  2009-05-07       Impact factor: 4.147

7.  Obesity treatment by epigallocatechin-3-gallate-regulated bile acid signaling and its enriched Akkermansia muciniphila.

Authors:  Lili Sheng; Prasant Kumar Jena; Hui-Xin Liu; Ying Hu; Nidhi Nagar; Denise N Bronner; Matthew L Settles; Andreas J Bäumler; Yu-Jui Yvonne Wan
Journal:  FASEB J       Date:  2018-06-08       Impact factor: 5.191

8.  Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry.

Authors:  Hiroki Takahashi; Kosuke Kai; Yoko Shinbo; Kenichi Tanaka; Daisaku Ohta; Taku Oshima; Md Altaf-Ul-Amin; Ken Kurokawa; Naotake Ogasawara; Shigehiko Kanaya
Journal:  Anal Bioanal Chem       Date:  2008-06-16       Impact factor: 4.142

9.  Oleocanthal-rich extra virgin olive oil demonstrates acute anti-platelet effects in healthy men in a randomized trial.

Authors:  Karan Agrawal; Eleni Melliou; Xueqi Li; Theresa L Pedersen; Selina C Wang; Prokopios Magiatis; John W Newman; Roberta R Holt
Journal:  J Funct Foods       Date:  2017-07-03       Impact factor: 4.451

10.  Investigation of metabolomic blood biomarkers for detection of adenocarcinoma lung cancer.

Authors:  Johannes F Fahrmann; Kyoungmi Kim; Brian C DeFelice; Sandra L Taylor; David R Gandara; Ken Y Yoneda; David T Cooke; Oliver Fiehn; Karen Kelly; Suzanne Miyamoto
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2015-08-17       Impact factor: 4.254

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