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  Multi-omic profiles of human non-alcoholic fatty liver disease tissue highlight heterogenic phenotypes.

Wruck, W., Kashofer, K., Rehman, S., Daskalaki, A., Berg, D., Gralka, E., et al. (2015). Multi-omic profiles of human non-alcoholic fatty liver disease tissue highlight heterogenic phenotypes. Scientific Data, 2: 150068.

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sdata201568.pdf (Verlagsversion), 2MB
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2015-10-20
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This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0 Metadata associated with this Data Descriptor is available at http://www.nature.com/sdata/ and is released under the CC0 waiver to maximize reuse.
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 Urheber:
Wruck, Wasco1, Autor
Kashofer, Karl2, Autor
Rehman, Samrina3, Autor
Daskalaki, Andriani4, Autor           
Berg, Daniela5, Autor
Gralka, Ewa6, Autor
Jozefczuk, Justyna7, Autor           
Drews, Katharina7, Autor           
Pandey, Vikash4, Autor           
Regenbrecht, Christian8, Autor
Wierling, Christoph K.4, Autor           
Turano, Paola6, Autor
Korf, Ulrike5, Autor
Zatloukal, Kurt2, Autor
Lehrach, Hans9, Autor           
Westerhoff, Hans V.10, Autor
Adjaye, James1, 7, Autor           
Affiliations:
1Medical Faculty, Institute for Stem Cell Research and Regenerative Medicine, Heinrich Heine University, , 40225 Düsseldorf, Germany , ou_persistent22              
2Institute of Pathology, Medical University of Graz, , Graz 8036, Austria , ou_persistent22              
3The Manchester Centre for Integrative Systems Biology, Manchester Institute of Biotechnology, University of Manchester,, Manchester M1 7DN, UK , ou_persistent22              
4Systems Biology (Christoph Wierling), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479656              
5ion of Molecular Genome Analysis, German Cancer Research Center (DKFZ), , 69120 Heidelberg, Germany , ou_persistent22              
6Magnetic Resonance Center (CERM), University of Florence, , 50019 Florence, Italy , ou_persistent22              
7Molecular Embryology and Aging (James Adjaye), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479654              
8Institute for Pathology & Comprehensive Cancer Center, Cancer Stem Cell Group, Charité—Universitätsmedizin, , 10117 Berlin, Germany, ou_persistent22              
9Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433550              
10 The Manchester Centre for Integrative Systems Biology, Manchester Institute of Biotechnology, University of Manchester, Manchester M1 7DN, UK Netherlands Institute for Systems Biology, VU University Amsterdam, HV NL-1081 Amsterdam, The Netherlands Synthetic Systems Biology, Swammerdam Institute for Life Sciences, University of Amsterdam, , 1018 WS Amsterdam, The Netherlands , ou_persistent22              

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Schlagwörter: Gene expression analysis • Metabolomics • Non-alcoholic fatty liver disease • Systems biology
 Zusammenfassung: Non-alcoholic fatty liver disease (NAFLD) is a consequence of sedentary life style and high fat diets with an estimated prevalence of about 30% in western countries. It is associated with insulin resistance, obesity, glucose intolerance and drug toxicity. Additionally, polymorphisms within, e.g., APOC3, PNPLA3, NCAN, TM6SF2 and PPP1R3B, correlate with NAFLD. Several studies have already investigated later stages of the disease. This study explores the early steatosis stage of NAFLD with the aim of identifying molecular mechanisms underlying the etiology of NAFLD. We analyzed liver biopsies and serum samples from patients with high- and low-grade steatosis (also pre-disease states) employing transcriptomics, ELISA-based serum protein analyses and metabolomics. Here, we provide a detailed description of the various related datasets produced in the course of this study. These datasets may help other researchers find new clues for the etiology of NAFLD and the mechanisms underlying its progression to more severe disease states.

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Sprache(n): eng - English
 Datum: 2015-03-162015-10-202015-12-08
 Publikationsstatus: Online veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
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Titel: Scientific Data
  Kurztitel : Sci. Data
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: London, United Kingdom : Nature Publishing Group
Seiten: - Band / Heft: 2 Artikelnummer: 150068 Start- / Endseite: - Identifikator: DOI: 10.1038/sdata.2015.68
CoNE: https://pure.mpg.de/cone/journals/resource/2052-4463