The poly-omics of ageing through individual-based metabolic modelling

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    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 languageEnglish
    Article number415
    JournalBMC Bioinformatics
    Volume19
    Issue number(Suppl 14)
    DOIs
    Publication statusPublished - 20 Nov 2018

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