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

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
Big data phenotyping in rare diseases: some ethical issues.
Journal article

Hallowell N. et al, (2019), Genetics in medicine : official journal of the American College of Medical Genetics, 21, 272 - 274
Next-generation phenotyping using computer vision algorithms in rare genomic neurodevelopmental disorders.
Journal article

van der Donk R. et al, (2018), Genetics in medicine : official journal of the American College of Medical Genetics
Deep clinical and biological phenotyping of the preterm birth and small for gestational age syndromes: The INTERBIO-21st Newborn Case-Control Study protocol
Journal article

Kennedy S. et al, (2018)
Turning a Blind Eye: Explicit Removal of Biases and Variation from Deep Neural Network Embeddings
Conference paper

Alvi M. et al, (2018)

More publications