We computationally interrogate rare disease-associated missense variants from within Genomics England’s 100,000 genomes data resource (led by Prof. Smedley and Dr. David, and in collaboration with Genomics England). We then apply algorithmic atomistic modelling to prioritize functional sites (led by Dr. David, Prof. Barahona and Prof. Yaliraki).

We generate new bioinformatic tools and process automation workflows for scalable and efficient engineering of the human proteome (led by Dr. Storch, Prof. Freemont and Dr. Child). 

Combining the outputs of our analysis, modeling & prediction with our automated engineering workflows we interpret the contribution of rare disease-associated missense variants to protein function, in live cells, at scale, and in high throughput (Dr. Storch, Prof. Freemont, Dr. Child and Prof. Tate). 

We then undertake rigourous disease-appropriate orthogonal validation of variant functional annotations (led by Dr. Storch, Prof. Freemont, Dr. Child and Prof. Tate).

Maximizing user access is a key aspect of our functional genomics cluster. We work toward data harmonization enabling stable data integration for researcher, clinician, and patient benefit (led by Prof. Smedley, Dr. David, Prof. Barahona, Prof. Yaliraki, Dr. Martin and Dr. Stephenson).