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
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 learningDoctor in the Loop
Improve learning efficiency by closing the loopQualifEye
Unsupervised representation learning approach for image quality evaluationSynthEye
Creating synthetic retinal image augmentations with deep learningEye-archical Tissue Segmentation
Using a hierarchical probabilistic framework to identify retinal tissue layersEye2Gene
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 imagingNote2Gene
Extracting genetic information from clinical notesOur Team
Nikolas Pontikos
Principal Investigator
Howard Maile
MPhil Medical Imaging And AI
Anita Szabo
Bioinformatics Research Assistant
William Woof
Postdoc Medical Imaging and AI
Advaith Yoga Veturi
Honorary Research Assistant Medical Imaging and AI
Quang Nguyen
MRes/PhD student
Dr Olivia Li
Honorary Clinical Research Fellow
Tianyi Liao
Honorary Research Assistant, Genetics of Human Disease
Nathaniel Kabiri
Honorary Research Assistant, Biochemistry
Yichen Liu
AI Research Assistant
Lynn Kandakji
PhD Medical Imaging And AI
Biraja Prasad Ghoshal
Honorary postdoctoral fellowWe 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