SOURCE-LINKED INTELLIGENCE
Understanding individual heterogeneity in ageing from stochastic dynamics of sigma factor regulatory network in bacteria
rpret expression and demographic signals for damage and ageing. I will combine the knowledge and methods from the disciplines of molecular biology, genetics, fluorescent microscopy and microfluidics, machine learning, population and evolutionary dynamics and mathematical modelling to shed light on the link from stochastic expression dynamics in sigma factor regulatory network towards individual variations observed in ageing fates. bacterial ageing, individual heterogeneity, biodemography, evolutionary demography, theoretical biology, mathematical biology, gene networks, sigma factor regulatory network, bacteria
Read original source ↗ Open in workspace
- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 189687.36
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T00:21:03.701Z. This is not the publication date.