Abstract
Ageing can be classified in two different ways, chronological ageing and biological ageing. While chronological age is a measure of the time that has passed since birth, biological (also known as transcriptomic) ageing is defined by how time and the environment affect an individual in comparison to other individuals of the same chronological age. Recent research studies have shown that transcriptomic age is associated with certain genes, and that each of those genes has an effect size. Using these effect sizes we can calculate the transcriptomic age of an individual from their age-associated gene expression levels. The limitation of this approach is that it does not consider how these changes in gene expression affect the metabolism of individuals and hence their observable cellular phenotype.
Original language | English |
---|---|
Article number | 415 |
Number of pages | 20 |
Journal | BMC Bioinformatics |
Volume | 19 |
Issue number | (Suppl 14) |
DOIs | |
Publication status | Published - 20 Nov 2018 |
Fingerprint
Dive into the research topics of 'The poly-omics of ageing through individual-based metabolic modelling'. Together they form a unique fingerprint.Profiles
-
Claudio Angione
- Department of Computing & Games - Professor of Artificial Intelligence
- Centre for Digital Innovation
Person: Professorial, Academic