(2024)
Deep learning-based characterization of neutrophil activation phenotypes in ex vivo human Candida blood infections.
Comput Struct Biotechnol J 23,
1260-1273.
Jan-Philipp Praetorius
Angewandte Systembiologie · FungiNet / JSMC +49 3641 532-1592 jan-philipp.praetorius@leibniz-hki.deCurriculum 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
(2023)
IMFSegNet: Cost-effective and objective quantification of intramuscular fat in histological sections by deep learning.
Comput Struct Biotechnol J 21,
3696-3704.
(2022)
Automated characterisation of neutrophil activation phenotypes in ex vivo human Candida blood infections.
Comput Struct Biotechnol J 20,
2297-2308.
(2021)
Enhanced segmentation of label-free cells for automated migration and interaction tracking.
Cytometry A 99(12),
1218-1229.
(2021)
Comparative assessment of immune evasion mechanisms in human whole-blood infection assays by a systems biology approach.
PLOS One 16(4),
e0249372.