Clemens Peiter

ORCID: 0009-0008-0140-488X
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About
Contact & Profiles
Research Areas
  • Neural Networks and Applications
  • COVID-19 Clinical Research Studies
  • SARS-CoV-2 and COVID-19 Research
  • Long-Term Effects of COVID-19
  • Gene Regulatory Network Analysis
  • Control Systems and Identification
  • COVID-19 epidemiological studies

University of Bonn
2023-2024

Abstract Non-linear mixed-effects models are a powerful tool for studying heterogeneous populations in various fields, including biology, medicine, economics, and engineering. Here, the aim is to find distribution over parameters that describe whole population using model can generate simulations an individual of population. However, fitting these distributions data computationally challenging if description individuals complex large. To address this issue, we propose novel machine...

10.1101/2023.08.22.554273 preprint EN cc-by bioRxiv (Cold Spring Harbor Laboratory) 2023-08-23

<title>Abstract</title> Vaccine breakthrough infections with SARS-CoV-2 Omicron induced a higher level of protection compared to triple vaccination and contributed herd immunity on population level. To address the underlying immunological mechanisms, we studied evolution SARS-CoV-2-specific antibody Tcell responses during upon infection in Bavarian residents between February 2021 December 2022. Further, investigated temporal distance completed break-through infection, as well any occurring...

10.21203/rs.3.rs-3411238/v1 preprint EN cc-by Research Square (Research Square) 2023-10-06
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