Ed Curry leads the Bioinformatics Hub in the Division of Cancer at Imperial College. His research group works on 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. One aspect of this work involves development of methodology for the sophisticated integration of multiple molecular datasets.
Another area of Ed's bioinformatics work focuses on 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 is senior tutor for the Cancer Informatics MRes programme, and lectures on courses across the Faculty of Medicine.
- Adaptive Binarization of Microarrays
- Genetic Algorithm Framework for Subspace Pattern Mining
- Gene expression state modelling for compendium-based interpretation of microarray data
- Localized Co-Dependency Analysis
- Finding transcription factors with ChIP-seq peaks enriched at genomic regions featuring aberrant chromatin compartmentalization (inferred from DNA methylation data)
et al., 2017, WWOX sensitises ovarian cancer cells to paclitaxel via modulation of the ER stress response, Cell Death & Disease, Vol:8, ISSN:2041-4889
et al., 2017, Jmjd2c facilitates the assembly of essential enhancer-protein complexes at the onset of embryonic stem cell differentiation, Development, Vol:144, ISSN:0950-1991, Pages:567-579
Simmonds P, Loomis E, Curry E, 2017, DNA methylation-based chromatin compartments and ChIP-seq profiles reveal transcriptional drivers of prostate carcinogenesis, Genome Medicine, Vol:9
et al., 2015, LARP1 post-transcriptionally regulates mTOR and contributes to cancer progression, Oncogene, Vol:34, ISSN:0950-9232, Pages:5025-5036
et al., 2015, Epigenome-wide association study reveals decreased average methylation levels years before breast cancer diagnosis, Clinical Epigenetics, Vol:7, ISSN:1868-7083