Machine Learning Meets Epigenetics: Investigating Links Between Facial Phenotypes and the Infant Epigenome in Rural Gambia

Andrew King (primary)
Biomedical Engineering
King's College London
Matt Silver (secondary)
Population Health
London School of Hygiene and Tropical Medicine

Abstract

Epigenetics describes how nuclear DNA is modified to direct gene expression. Epigenetics research suggests that inadequate diet at the time of conception can lead to errors in the embryonic epigenome, with potential consequences for child development. The face is a powerful integrative signature of early developmental errors, so facial analysis offers an intriguing way to learn more about the role of epigenetics in development. This project will use a database of facial scans acquired from children in rural Gambia and the latest machine learning techniques to investigate links between facial phenotypes, epigenetics and seasonal differences in diet at conception.


References

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BBSRC Area
Genes, development and STEM* approaches to biology
Area of Biology
DevelopmentGenetics
Techniques & Approaches
BioinformaticsGeneticsImage ProcessingMathematics / Statistics