Translational Genomics
We work at the interface of research and translation, with many ongoing clinical collaborations. We rely on experimental and computational genomics to advance our translational research but do not shy away from other approaches.
We also contribute to the academic leadership of the Genomic Medicine Theme in the NIHR GOSH Biomedical Research Centre,, and have a growing interest in the social impact of AI to genomic diagnosis. Further, we contribute to genomic services, providing academic leadership to UCL Genomics and the Genomics Science Technology Platform at UCL. Finally, we teach computational genomics in our MSc in Personalised Medicine and Novel Therapies.
We also occasionally provide consultations on all things genomics.
If you are interested in what we do, please check our job openings or consider applying to a fellowship with us.
Research Interests
We are interested in accelerating the diagnosis, prognosis, treatment and modelling of various rare diseases and cancers in children. To this end, we leverage established and novel genomic technologies and their computational analysis, to explore new clinical possibilities.
We are particularly keen on translational approaches at single-cell resolution, which we apply to assess disease heterogeneity and the quality of new disease models, tissues and organs. We also assess genomic risks from new therapies, including the unwanted acquisition of deleterious mutations when engineering new tissues, editing genomes or introducing new genes. Further, we apply population genomics and support metagenomic approaches to understand micronutrient deficiencies in global health as well as infection.
In this regard, we have supported the tracking of mutations in the spread of COVID-19 in the UK, through genomic sequencing.
Recent Publications
McGlacken-Byrne et al. (includes T Xenakis)
Mapping the anatomical and transcriptional landscape of early human fetal ovary development
bioRxiv
Gerli et al. (includes T Xenakis)
bioRxiv
Hall and Castellano
Dawnn: single-cell differential abundance with neural networks
bioRxiv
Bea-Mascato et al.
bioRxiv
Rees et al.
Ancient loss of catalytic selenocysteine spurred convergent adaptation in a mammalian oxidoreductase
bioRxiv
Puigdevall et al.
Effects of somatic mutations on cellular differentiation in iPSC models of neurodevelopment
Cell Genomics, 3, 100280 (2023)
Morfopoulou et al.
Genomic investigations of acute hepatitis of unknown aetiology in children
Nature, 617, 564–573 (2023)
Jayarajan et al.
Cells, 12, 346 (2023)
Michelozzi et al.
Blood Advances, 7, 1725–1738 (2023)