Genomic & Clinical Data Analysis

Decision Support Systems for rare diseases.

Our lab is interested in the analysis of health care data to provide personalised care. We jointly analyse genetics, medical imaging and text data to develop decision support systems for diagnosis, prognosis and treatment. Our focus has mostly been on rare eye diseases but our methodology is widely applicable to rare genetic diseases.

Our lab currently works across the following organisations:

Rare Eye Disease Research

Rare eye diseases are a leading cause of blindness in children and young adults in the UK. These include diseases affecting the retina, the light-sensitive tissue at the back of the eye, or the cornea, the transparent tissue at the front of the eye that focuses light. Patients with rare eye diseases are a vulnerable population with a decreased quality of life. This is often because they are diagnosed late, not adequately treated or followed-up. Our lab's research aims to improve diagnosis, prognosis, treatment and care of these patients by developing software to enable healthcare professionals to detect disease faster and make patient-centred decisions about their treatment and care.

Research Projects

Enhancing Care and Anomalies Detection in a Common Eye Disease with Deep Learning

Investigation of novel protein structures in human disease

Investigating novel uncharacterised protein sequences in health and disease u...

Genetic Landscape of Rare Disease Patients

Analysing a database of 6000+ genetic patients with rare diseases collected s...

Alignment in Complex Genomic Regions

Developing artificial chromosomes reference panels for alignment in complex r...

BayesConformPred

Leveraging conformal prediction with estimated uncertainty for disease detect...

EyeNomaly

Anomaly detection in medical images using unsupervised learning

Doctor in the Loop

Improve learning efficiency by closing the loop

QualifEye

Unsupervised representation learning approach for image quality evaluation

SynthEye

Creating synthetic retinal image augmentations with deep learning

Eye-archical Tissue Segmentation

Using a hierarchical probabilistic framework to identify retinal tissue layers

Eye2Gene

Decision support systems for genetic diagnosis of inherited retinal diseases.

EyeCon

Decision support systems for keratoconus and other corneal ectasias.

Phenopolis Genomic Browser

A genetic browser than integrates with the Human Phenotype Ontology.

KeraScreen

Detection of subclinical keratoconus from corneal imaging

EyeNote

Extracting genetic information from clinical notes

Our Team

Meet the Team

We are always eager for hard-working & motivated people to come and work with us.

If you're interested in joining us, please send Nikolas Pontikos a quick email with a CV and personal statement