Kopczynski, D., Ejsing, C. S., McDonald, J. G., Bamba, T., Baker, E. S., Bertrand-Michel, J., Brügger, B., Coman, C., Ellis, S. R., Garrett, T. J., Griffiths, W. J., Guan, X. L., Han, X., Höring, M., Holčapek, M., Hoffmann, N., Huynh, K., Lehmann, R., Jones, J. W., ... Liebisch, G. (2024). The lipidomics reporting checklist a framework for transparency of lipidomic experiments and repurposing resource data. Journal of Lipid Research, 65(9), Article 100621. https://doi.org/10.1016/j.jlr.2024.100621

Witting, M., Malik, A., Leach, A., Bridge, A., Aimo, L., Conroy, M. J., O’Donnell, V. B., Hoffmann, N., Kopczynski, D., Giacomoni, F., Paulhe, N., Gassiot, A. C., Poupin, N., Jourdan, F., & Bertrand-Michel, J. (2024). Challenges and perspectives for naming lipids in the context of lipidomics. Metabolomics, 20(1), Article 15. https://doi.org/10.1007/s11306-023-02075-x

Heimerl, S., Höring, M., Kopczynski, D., Sigruener, A., Hart, C., Burkhardt, R., Black, A., Ahrends, R., & Liebisch, G. (2023). Quantification of bulk lipid species in human platelets and their thrombin-induced release. Scientific Reports, 13(1), Article 6154. https://doi.org/10.1038/s41598-023-33076-4

Kopczynski, D., Hoffmann, N., Troppmair, N., Coman, C., Ekroos, K., Kreutz, M. R., Liebisch, G., Schwudke, D., & Ahrends, R. (2023). LipidSpace: Simple Exploration, Reanalysis, and Quality Control of Large-Scale Lipidomics Studies. Analytical Chemistry, 95(41), 15236-15244. https://doi.org/10.1021/acs.analchem.3c02449

Troppmair, N., Kopczynski, D., Assinger, A., Lehmann, R., Coman, C., & Ahrends, R. (2023). Accurate Sphingolipid Quantification Reducing Fragmentation Bias by Nonlinear Models. Analytical Chemistry, 95(41), 15227-15235. https://doi.org/10.1021/acs.analchem.3c02445

de Jonckheere, B., Kollotzek, F., Münzer, P., Göb, V., Fischer, M., Mott, K., Coman, C., Troppmair, N. N., Manke, M. C., Zdanyte, M., Harm, T., Sigle, M., Kopczynski, D., Bileck, A., Gerner, C., Hoffmann, N., Heinzmann, D., Assinger, A., Gawaz, M., ... Ahrends, R. (2023). Critical shifts in lipid metabolism promote megakaryocyte differentiation and proplatelet formation. Nature Cardiovascular Research, 2(9), 835-852. https://doi.org/10.1038/s44161-023-00325-8

Vondrackova, M., Kopczynski, D., Hoffmann, N., & Kuda, O. (2023). LORA, Lipid Over-Representation Analysis Based on Structural Information. Analytical Chemistry, 95(34), 12600-12604. https://doi.org/10.1021/acs.analchem.3c02039

Chen, S., Liang, C., Li, H., Yu, W., Prothiwa, M., Kopczynski, D., Loroch, S., Fransen, M., & Verhelst, S. H. L. (2023). Pepstatin-Based Probes for Photoaffinity Labeling of Aspartic Proteases and Application to Target Identification. ACS Chemical Biology, 18(4), 686-692. https://doi.org/10.1021/acschembio.2c00946

Ni, Z., Wolk, M., Jukes, G., Espinosa, K. M., Ahrends, R., Aimo, L., Alvarez-Jarreta, J., Andrews, S., Andrews, R., Bridge, A., Clair, G. C., Conroy, M. J., Fahy, E., Gaud, C., Goracci, L., Hartler, J., Hoffmann, N., Kopczynski, D., Korf, A., ... Fedorova, M. (2023). Guiding the choice of informatics software and tools for lipidomics research applications. Nature Methods, 20(2), 193-204. https://doi.org/10.1038/s41592-022-01710-0

McDonald, J. G., Ejsing, C. S., Kopczynski, D., Holcapek, M., Aoki, J., Arita, M., Arita, M., Baker, E. S., Bertrand-Michel, J., Bowden, J. A., Brugger, B., Ellis, S. R., Fedorova, M., Griffiths, W. J., Han, X., Hartler, J., Hoffmann, N., Koelmel, J. P., Kofeler, H. C., ... Ekroos, K. (2022). Introducing the Lipidomics Minimal Reporting Checklist. Nature Metabolism, 4(9), 1086-1088. https://doi.org/10.1038/s42255-022-00628-3

Hoffmann, N., Mayer, G., Has, C., Kopczynski, D., Al Machot, F., Schwudke, D., Ahrends, R., Marcus, K., Eisenacher, M., & Turewicz, M. (2022). A Current Encyclopedia of Bioinformatics Tools, Data Formats and Resources for Mass Spectrometry Lipidomics. Metabolites, 12(7), Article 584. https://doi.org/10.3390/metabo12070584

Kopczynski, D., Hoffmann, N., Peng, B., Liebisch, G., Spener, F., & Ahrends, R. (2022). Goslin 2.0 Implements the Recent Lipid Shorthand Nomenclature for MS-Derived Lipid Structures. Analytical Chemistry, 94(16), 6097-6101. https://doi.org/10.1021/acs.analchem.1c05430

Kopczynski, D., Hentschel, A., Coman, C., Schebb, N. H., Hornemann, T., Mashek, D. G., Hartung, N. M., Shevchuk, O., Schott, H.-F., Lorenz, K., Torta, F., Burla, B., Zahedi, R. P., Sickmann, A., Kreutz, M. R., Ejsing, C. S., Medenbach, J., & Ahrends, R. (2020). Simple Targeted Assays for Metabolic Pathways and Signaling: A Powerful Tool for Targeted Proteomics. Analytical Chemistry, 92(20), 13672-13676. https://doi.org/10.1021/acs.analchem.0c02793

Kopczynski, D., Hoffmann, N., Peng, B., & Ahrends, R. (2020). Goslin: A Grammar of Succinct Lipid Nomenclature. Analytical Chemistry, 92(16), 10957-10960. https://doi.org/10.1021/acs.analchem.0c01690

Peng, B., Kopczynski, D., Pratt, B. S., Ejsing, C. S., Burla, B., Hermansson, M., Benke, P. I., Tan, S. H., Chan, M. Y., Torta, F., Schwudke, D., Meckelmann, S. W., Coman, C., Schmitz, O. J., MacLean, B., Manke, M.-C., Borst, O., Wenk, M. R., Hoffmann, N., & Ahrends, R. (2020). LipidCreator workbench to probe the lipidomic landscape. Nature Communications, 11(1), Article 2057. https://doi.org/10.1038/s41467-020-15960-z