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Publikationen 2023

  1. Noufal Y, Kringel D, Toennes SW, Dudziak R, and Lötsch J. Pharmacological data science perspective on fatal incidents of morphine treatment. Pharmacol Ther 2023 Jan;241:108312
  2. Sisignano M, and Geisslinger G. Rethinking the use of NSAIDs in early acute pain. Trends in Pharmacological Sciences 2023 Apr;44(4):193-195. doi: 10.1016/j.tips.2023.01.001
  3. Lötsch J, and Ultsch A. Recursive computed ABC (cABC) analysis as a precise method for reducing machine learning based feature sets to their minimum informative size. Sci Rep 2023 (accepted)
  4. Lötsch J, Mayer, B, and Kringel D. Machine learning analysis predicts a person’s sex based on mechanical but not thermal pain thresholds. Sci Rep 2023 (accepted)
  5. Knaup FH, Meyners C, Sugiarto WO, Wedel S, Springer M, Walz C, Geiger TM, Schmidt M, Sisignano M, and Hausch F. Structure-based discovery of a new selectivity-enabling motif for the FK506-binding protein 51. J Med Chem 2023 doi: 10.1021/acs.jmedchem.3c00249
  6. Lötsch J, and Ultsch A. Comments on the importance of visualizing the distribution of pain-related data. Eur J Pain 2023 (accepted)
  7. Wedel S, Hahnefeld L, Schreiber Y, Namendorf C, Heymann T, Uhr M, Schmidt MV, de Bruin N, Hausch F, Thomas D, Geisslinger G, and Sisignano M. SAFit2 ameliorates paclitaxel-induced neuropathic pain by reducing spinal gliosis and elevating pro-resolving lipid mediators. J Neuroinflammation 2023 (accepted)
  8. Lötsch J, and Ultsch A. Pitfalls of using multinomial regression analysis to identify class-structure relevant variables in biomedical datasets: Why a mixture of experts (MOE) approach is better. BiomedInformatics 2023 (accepted)