Publications

Okidoki, here now an up-to-date list of publications I (co-)authored, in chronological order, starting with the most recent (and beloved) ones.

  1. Krefting, J., Sen, P., David-Rus, D., Güldener, U., Hawe, J. S., … Schunkert, H. (2023). Use of big data from health insurance for assessment of cardiovascular outcomes. Front. Artif. Intell., 6. https://doi.org/10.3389/frai.2023.1155404
  2. Güldener, U., Kessler, T., von Scheidt, M., Hawe, Johann S., Gerhard, B., Maier, D., Lachmann, M., Laugwitz, K.-L., Cassese, S., Schömig, A.W., Kastrati, A., Schunkert, H. (2023). Machine Learning Identifies New Predictors on Restenosis Risk after Coronary Artery Stenting in 10,004 Patients with Surveillance Angiography. J. Clin. Med., 12, 2941. https://doi.org/10.3390/jcm12082941
  3. Hawe, Johann S., Saha, A., Waldenberger, M., . . . Heinig, M. (2022). Network reconstruction for trans acting genetic loci using multi-omics data and prior information. Genome Med 14, 125. https://doi.org/10.1186/s13073-022-01124-9
  4. Bauer, S., Eigenmann, J., Zhao, Y., Fleig, J., Hawe, Johann S., . . . Schunkert, H., von Scheidt, M. (2022). Identification of the Transcription Factor ATF3 as a Direct and Indirect Regulator of the LDLR. Metabolites. https://doi.org/10.3390/metabo12090840
  5. Hawe, Johann S., Wilson, R.., . . . Chambers, J. (2022). Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function. Nat Genet. https://doi.org/10.1038/s41588-021-00969-x
  6. Neiburga, K.D., Vilne, B., Bauer, S., Bongiovanni, D., Ziegler, T., Lachmann, M., Wengert, S., Hawe, Johann S., Güldener, U., … Schunkert, H., von Scheidt, M. (2021) Vascular Tissue Specific miRNA Profiles Reveal Novel Correlations with Risk Factors in Coronary Artery Disease. Biomolecules, 11, 1683. https://doi.org/10.3390/biom11111683
  7. Westerlund, Annie M., Hawe, Johann S., Heinig, Matthias, and Schunkert, Heribert. (2021) Risk Prediction of Cardiovascular Events by Exploration of Molecular Data with Explainable Artificial Intelligence, International Journal of Molecular Sciences 22, no. 19: 10291. https://doi.org/10.3390/ijms221910291
  8. Hawe, Johann S., Saha, A., Waldenberger, M., Kunze, S., Wahl, S., Mueller-Nurasyid, M., … Heinig, M. (2020). Network reconstruction for trans acting genetic loci using multi-omics data and prior information. BioRxiv, 2020.05.19.101592. https://doi.org/10.1101/2020.05.19.101592
  9. Quagliarini, F., Mir, A. A., Balazs, K., Wierer, M., Dyar, K. A., Jouffe, C., Makris, K., Hawe, Johann S.,… Uhlenhaut, N. H. (2019) Cistromic Reprogramming of the Diurnal Glucocorticoid Hormone Response by High-Fat Diet. Molecular Cell, 0(0). https://doi.org/10.1016/j.molcel.2019.10.007
  10. Hawe, Johann S., Theis, F. J., & Heinig, M. (2019). Inferring Interaction Networks From Multi-Omics Data. Frontiers in Genetics, 10, 535. https://doi.org/10.3389/fgene.2019.00535
  11. Küffner, R., Zach, N., Norel, R., Hawe, Johann S., Schoenfeld, D., Wang, L., . . . Leitner, M. L. (2015). Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression. Nat Biotechnol 33, 51–57. https://doi.org/10.1038/nbt.3051

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