MRC WIMM Centre for Computational Biology
Computational Biologist and Genomic Datascience Trainer
Dynamics of Transcriptional Regulation
I am a computational and molecular biologist focused on understanding the molecular dynamics of transcriptional regulation in mammalian tissues in response to fluctuating developmental, hormonal and circadian stimuli.
During my PhD studying the transcriptional effects of the pulsatile glucocorticoid hormones on the brain with Professor Stafford Lightman (FRS) and Dr Becky Conway-Campbell at the University of Bristol I quickly developed an passion for the field of genomics and its power to uncover the regulatory mechanisms that underly transcriptional regulation.
Realising that gaining advanced computational skills was going to be vital to my future research interests in 2014 I applied for a highly competitive MRC Training Fellowship in Computational Biology on the Computational Genomic Analysis Training (CGAT) programme directed by Professor Chris Ponting and Dr Andreas Heger at the University of Oxford. During this three-year fellowship I gained extensive training in software development, experimental design, project management, data stewardship, statistics and genomic analysis and worked on the analysis and integration of numerous genomic datasets (e.g. RNAseq, ChIPseq, ATACseq, promoter capture HiC) with research groups across the UK.
My current role allows me to split my time between my independent research projects investigating the dynamic regulation of chromatin architecture and gene expression in the brain and teaching on the Oxford Biomedical Data Science Programme. Given my own transition to computational biology from the wet-lab I am fully aware of challenges facing biological researchers in these fields and I am passionate about empowering researchers to gain computational skills, enabling them to confidently and responsibly analyse data, ensuring high quality and reproducible research.
CGAT-core: a python framework for building scalable, reproducible computational biology workflows
Cribbs AP. et al, (2019), F1000Research, 8, 377 - 377
Ultradian glucocorticoid exposure directs gene-dependent and tissue-specific mRNA expression patterns in vivo.
George CL. et al, (2017), Mol Cell Endocrinol, 439, 46 - 53
Glucocorticoids—timing, binding and environment
Lightman SL. and George CL., (2014), Nature Reviews Endocrinology, 10, 71 - 72
The HSP90 Molecular Chaperone Cycle Regulates Cyclical Transcriptional Dynamics of the Glucocorticoid Receptor and Its Coregulatory Molecules CBP/p300 During Ultradian Ligand Treatment
Conway-Campbell BL. et al, (2011), Molecular Endocrinology, 25, 944 - 954