PUB - Publikationen an der Universität Bielefeld

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• [20]
  

  2022 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2968524

  Ni, Z., et al., 2022. Guiding the choice of informatics software and tools for lipidomics research applications. Nature Methods .

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [19]
  

  2022 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2966976

  Ekroos, K., et al., 2022. Update on guidelines for lipidomics analysis and reporting. Journal of the American Oil Chemists' Society, 99(Suppl. 1), p 13-14.

  PUB | DOI | WoS
   
• [18]
  

  2022 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2965107

  McDonald, J.G., et al., 2022. Introducing the Lipidomics Minimal Reporting Checklist. Nature Metabolism .

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [17]
  

  2022 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2962357

  Kopczynski, D., et al., 2022. Goslin 2.0 Implements the Recent Lipid Shorthand Nomenclature for MS-Derived Lipid Structures. Analytical Chemistry, : acs.analchem.1c05430.

  PUB | DOI | Download (ext.) | WoS | PubMed | Europe PMC
   
• [16]
  

  2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2959919

  Borgmeyer, M., et al., 2021. Multiomics of synaptic junctions reveals altered lipid metabolism and signaling following environmental enrichment. Cell Reports, 37(1): 109797.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [15]
  

  2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2958747

  Kofeler, H.C., et al., 2021. Recommendations for Good Practice in Mass Spectrometry-Based Lipidomics. Journal of Lipid Research, 62: 100138.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [14]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2956707

  Peng, B., et al., 2020. LipidCreator workbench to probe the lipidomic landscape. Nature Communications, 11(1): 2057.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [13]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2956705

  Kopczynski, D., et al., 2020. Goslin: A Grammar of Succinct Lipid Nomenclature. Analytical Chemistry, 92(16), p 10957-10960.

  PUB | DOI | WoS | PubMed | Europe PMC | Preprint
   
• [12]
  

  2019 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2956709

  Wibberg, D., et al., 2019. The de.NBI / ELIXIR-DE training platform - Bioinformatics training in Germany and across Europe within ELIXIR. F1000Research, 8: 1877.

  PUB | DOI
   
• [11]
  

  2019 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2956712

  Hoffmann, N., et al., 2019. mzTab-M: A Data Standard for Sharing Quantitative Results in Mass Spectrometry Metabolomics. Analytical Chemistry, 91(5), p 3302-3310.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [10]
  

  2019 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2956711

  Hoffmann, N., Hartler, J., & Ahrends, R., 2019. jmzTab-M: A Reference Parser, Writer, and Validator for the Proteomics Standards Initiative mzTab 2.0 Metabolomics Standard. Analytical Chemistry, 91(20), p 12615-12618.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [9]
  

  2019 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2956710

  Stanstrup, J., et al., 2019. The metaRbolomics Toolbox in Bioconductor and beyond. Metabolites, 9(10): 200.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [8]
  

  2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2956713

  Peng, B., et al., 2018. Identification of key lipids critical for platelet activation by comprehensive analysis of the platelet lipidome. Blood, 132(5), p e1-e12.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [7]
  

  2017 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2956714

  Schwudke, D., et al., 2017. Lipidomics informatics for life-science. Journal of Biotechnology, 261, p 131-136.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [6]
  

  2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2715682

  Henning, P., et al., 2015. Maui-VIA: a user-friendly software for visual identification, alignment, correction, and quantification of gas chromatography–mass spectrometry data. Frontiers in Bioengineering and Biotechnology, 2(84), p 84.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [5]
  

  2014 | Bielefelder E-Dissertation | PUB-ID: 2677466

  Hoffmann, N., 2014. Computational methods for high-throughput metabolomics, Bielefeld: Universität Bielefeld.

  PUB | PDF
   
• [4]
  

  2014 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2643941

  Hoffmann, N., et al., 2014. BiPACE 2D – Graph-based multiple alignment for comprehensive two-dimensional gas chromatography–mass spectrometry. Bioinformatics, 30(7), p 988-995.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [3]
  

  2012 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2517239

  Hoffmann, N., et al., 2012. Combining peak- and chromatogram-based retention time alignment algorithms for multiple chromatography-mass spectrometry datasets. BMC Bioinformatics, 13(1): 21.

  PUB | PDF | DOI | WoS | PubMed | Europe PMC
   
• [2]
  

  2012 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2468382

  Hoffmann, N., & Stoye, J., 2012. Generic Software Frameworks for GC-MS Based Metabolomics. In U. Roessner, ed. Metabolomics. InTech, pp. 73-98.

  PUB | PDF | DOI | Download (ext.)
   
• [1]
  

  2009 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 1591319

  Hoffmann, N., & Stoye, J., 2009. ChromA: signal-based retention time alignment for chromatography-mass spectrometry data. Bioinformatics, 25(16), p 2080-2081.

  PUB | DOI | WoS | PubMed | Europe PMC