Machine learning and data-driven inverse modeling of metabolomics unveil key process of active aging
- Author(s)
- Jiahang Li, Martin Brenner, Iro Pierides, Barbara Wessner, Bernhard Franzke, Eva-Maria Strasser, Steffen Waldherr, Karl-Heinz Wagner, Wolfram Weckwerth
- Organisation(s)
- Functional and Evolutionary Ecology, Department of Sport and Human Movement Science, Department of Nutritional Sciences, Research Platform Vienna Metabolomics Center
- External organisation(s)
- Sozialmedizinisches Zentrum Süd – Kaiser-Franz-Josef-Spital
- Journal
- bioRxiv : the preprint server for biology
- ISSN
- 2692-8205
- DOI
- https://doi.org/10.1101/2024.08.27.609825
- Publication date
- 08-2024
- Austrian Fields of Science 2012
- 302020 Gerontology, 106044 Systems biology, 303009 Nutritional sciences, 303028 Sport science
- Portal url
- https://ucrisportal.univie.ac.at/en/publications/96b27ca5-4b15-4830-9926-481e0c4058cf