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
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., 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
et al., 2015, A putative biomarker signature for clinically effective AKT inhibition: correlation of in vitro, in vivo and clinical data identifies the importance of modulation of the mTORC1 pathway, Oncotarget, Vol:6, ISSN:1949-2553, Pages:41736-41749
et al., 2015, Dual EZH2 and EHMT2 histone methyltransferase inhibition increases biological efficacy in breast cancer cells, Clinical Epigenetics, Vol:7, ISSN:1868-7083