Christoffer Nellåker

Research Fellow, Nuffield Department of Obstetrics and Gynaecology

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

Mining faces from biomedical literature using deep learning
Conference paper

Dawson M. et al, (2017), ACM-BCB 2017 - Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, 562 - 567
Clinical and molecular consequences of disease-associated de novo mutations in SATB2
Journal article

Nellaker C. et al, (2017), Genetics in Medicine
Clinical and molecular consequences of disease-associated de novo mutations in SATB2
Journal article

Nellaker C. et al, (2017), Genetics in Medicine
The RNA-editing enzyme ADAR1 controls innate immune responses to RNA.
Journal article

Mannion NM. et al, (2014), Cell Rep, 9, 1482 - 1494
Genetic heterogeneity in Cornelia de Lange syndrome (CdLS) and CdLS-like phenotypes with observed and predicted levels of mosaicism.
Journal article

Ansari M. et al, (2014), J Med Genet, 51, 659 - 668

More publications