Christoffer Nellåker

Research Fellow, Nuffield Department of Women's & Reproductive Health

Rare diseases are individually rare but collectively very common. It is estimated that one in seventeen people have some type of rare disease. Clinicians frequently look for characteristic changes in facial features to help find a diagnosis.

Dr. Nellåker’s group is translating the latest developments in computer vision and computational biology to aid diagnosis of rare diseases. The work is a collaborative effort to apply the latest techniques from facial recognition research for disease phenotyping. The aim is to bring this to clinical use to help narrow down the search for a correct diagnosis and to be used together with genome sequencing to identify mutations causing disease.

Key publications

Diagnostically relevant facial gestalt information from ordinary photos.
Journal article

Ferry Q. et al, (2014), eLife, 3

Recent publications

Mutation-specific pathophysiological mechanisms define different neurodevelopmental disorders associated with SATB1 dysfunction.
Journal article

den Hoed J. et al, (2021), American journal of human genetics
The case for open science: rare diseases.
Journal article

Rubinstein YR. et al, (2020), JAMIA open, 3, 472 - 486
Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits.
Journal article

Glastonbury CA. et al, (2020), PLoS computational biology, 16
A call for global action for rare diseases in Africa.
Journal article

Baynam GS. et al, (2020), Nature genetics, 52, 21 - 26
Missense Variants in the Histone Acetyltransferase Complex Component Gene TRRAP Cause Autism and Syndromic Intellectual Disability.
Journal article

Cogné B. et al, (2019), American journal of human genetics, 104, 530 - 541

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