Summary
From October 2019, Ed is based full-time at GSK R&D in Stevenage, UK. He maintains some teaching commitments and research collaborations at Imperial College London, and can still be reached through his Imperial College email address.
His research at Imperial involves the analysis of datasets from a wide range of platforms profiling the genetic, epigenetic and transcriptional state of cells during cancer development and acquisition of drug resistance. A key part of this work is identifying biologically informative patterns that exist within subsets of large, heterogeneous datasets. This is particularly important when studying cancers, as mechanisms of carcinogenesis and drug resistance are rarely conserved across across all patients with a particular disease, or indeed even across all cells from an individual tumour.
Ed helped develop the curriculum for the Cancer Informatics MRes programme, and the Genetics and Genomics module for the BSc in Medical Biosciences. He is happy to answer queries regarding these courses, but in the first instance you should contact James Flanagan (for Cancer Informatics) or Andy Porter (for Genetics & Genomics).
Software:
- Finding transcription factors with ChIP-seq peaks enriched at genomic regions featuring aberrant chromatin compartmentalization (inferred from DNA methylation data)
- Genetic Algorithm Framework for Subspace Pattern Mining
- Gene expression state modelling for compendium-based interpretation of microarray data
- Localized Co-Dependency Analysis
- Adaptive Binarization of Microarrays
Publications
Journals
Gallon J, Loomis E, Curry E, et al., 2021, Chromatin accessibility changes at intergenic regions associates with ovarian cancer drug resistance, Clinical Epigenetics, ISSN:1868-7083
Lu H, Arshad M, Thornton A, et al., 2019, A mathematical-descriptor of tumor-mesoscopic-structure from computed-tomography images annotates prognostic and molecular-phenotypes of epithelial ovarian cancer, Nature Communications, Vol:10, ISSN:2041-1723
Cunnea P, Gorgy T, Petkos K, et al., 2018, Clinical value of bioelectrical properties of cancerous tissue in advanced epithelial ovarian cancer patients, Scientific Reports, Vol:8, ISSN:2045-2322, Pages:1-12
Brown R, Curry E, Zeller C, et al., 2018, Genes predisposed to DNA hypermethylation during acquired resistance to chemotherapy are identified in ovarian tumors by bivalent chromatin domains at initial diagnosis, Cancer Research, Vol:78, ISSN:1538-7445, Pages:1383-1391
Janczar S, Nautiyal J, Xiao Y, et al., 2017, WWOX sensitizes ovarian cancer cells to paclitaxel via modulation of the ER stress response, Cell Death & Disease, Vol:8, ISSN:2041-4889