- Webber Group Research Group
MRC Programme Leader
I obtained my PhD in 2003 from the European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton Cambridge and from the Department of Genetics, Cambridge University. Afterwards I returned to Oxford to work with Prof. Chris Ponting on most of the major large-scale genome projects of the last decade. My interest in synteny breaks from those projects led to an interest in copy number variation, and in turn to the role of genetic variation in disease.
I am strongly collaborative with many European and International partnerships, especially through the Genetics of Cognitive Dysfunction (Gencodys) Consortium and through the IMI StemBANCC consortium, where I lead the Data Interpretation package. If you think we could do something fun together, drop me an email.
The clustering of functionally related genes contributes to CNV-mediated disease.
Andrews T. et al, (2015), Genome Res, 25, 802 - 813
Synergistic interactions between Drosophila orthologues of genes spanned by de novo human CNVs support multiple-hit models of autism.
Grice SJ. et al, (2015), PLoS Genet, 11
Unbiased functional clustering of gene variants with a phenotypic-linkage network.
Honti F. et al, (2014), PLoS Comput Biol, 10
The roles of FMRP-regulated genes in autism spectrum disorder: single- and multiple-hit genetic etiologies.
Steinberg J. and Webber C., (2013), Am J Hum Genet, 93, 825 - 839
Network topologies and convergent aetiologies arising from deletions and duplications observed in individuals with autism.
Noh HJ. et al, (2013), PLoS Genet, 9
Transcriptomic profiling of purified patient-derived dopamine neurons identifies convergent perturbations and therapeutics for Parkinson's disease.
Sandor C. et al, (2017), Hum Mol Genet, 26, 552 - 566
Whole-exome sequencing of 228 patients with sporadic Parkinson's disease.
Sandor C. et al, (2017), Sci Rep, 7
Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine.
Gormley P. et al, (2016), Nat Genet, 48, 856 - 866
Systematic Phenomics Analysis Deconvolutes Genes Mutated in Intellectual Disability into Biologically Coherent Modules.
Kochinke K. et al, (2016), Am J Hum Genet, 98, 149 - 164
Haploinsufficiency predictions without study bias.
Steinberg J. et al, (2015), Nucleic Acids Res, 43