Jan-Philipp Praetorius

Jan-Philipp Praetorius

Angewandte Systembiologie · FungiNet / JSMC

In Elternzeit

+49 3641 532-1592 jan-philipp.praetorius@leibniz-hki.de

Curriculum vitae

Forschungsschwerpunkte
  • Automatisierte Analyse von mikroskopischen Bilddaten der Wirt-Pathogen Interaktion
Wissenschaftlicher Werdegang
seit 2019 Doktorand im Fach Bioinformatik am Hans-Knöll-Institut
2019 M.Sc. in Computational and Data Science an der Friedrich-Schiller-Universität Jena
2016 B.Sc. in Wirtschaftsinformatik an der Friedrich-Schiller-Universität Jena

Publikationen

Sarkar A, Praetorius JP, Figge MT# (2024) Deep learning-based characterization of neutrophil activation phenotypes in ex vivo human Candida blood infections. Comput Struct Biotechnol J 23, 1260-1273.
Walluks K*, Praetorius JP*, Arnold D#, Figge MT# (2024) Impact of functional electrical stimulation on nerve-damaged muscles by quantifying fat infiltration using deep learning. Sci Rep 14(1), 12158.
Praetorius JP, Walluks K, Svensson CM, Arnold D, Figge MT# (2023) IMFSegNet: Cost-effective and objective quantification of intramuscular fat in histological sections by deep learning. Comput Struct Biotechnol J 21, 3696-3704.
Belyaev I*, Marolda A*, Praetorius JP, Sarkar A, Medyukhina A, Hünniger K, Kurzai O, Figge MT (2022) Automated characterisation of neutrophil activation phenotypes in ex vivo human Candida blood infections. Comput Struct Biotechnol J 20, 2297-2308.
Belyaev I*, Praetorius JP*, Medyukhina A, Figge MT (2021) Enhanced segmentation of label-free cells for automated migration and interaction tracking. Cytometry A 99(12), 1218-1229.
Lehnert T, Prauße MTE, Hünniger K, Praetorius JP, Kurzai O, Figge MT (2021) Comparative assessment of immune evasion mechanisms in human whole-blood infection assays by a systems biology approach. PLOS One 16(4), e0249372.