Contact information
Big Data Institute, Old Road Campus, Headington, Oxford, OX3 7LF
AI against Prostate Cancer
The Prostate Pod met Dan Brewer and Dan Woodcock for a chat about how artificial intelligence is a new frontier against prostate cancer. Listen to the podcast episode on Spotify
Dan Woodcock
Associate Professor of Translational Data Science
- Group Leader
The focus of our group is the development and application of machine learning and statistical methods to multi-modal data sets that can reveal information that conventional techniques cannot. We mainly work in cancer, where a common interest within the group is to uncover why certain subgroups of patients are susceptible or resistant to particular treatments; a crucial part of the puzzle in the push toward personalised medicine.
Dan is involved in a number of research projects within Oxford, including leading the multimodal data analysis in the COMBATcancer project run through Oxford Cancer and co-leading the Oncology workstream of the Cartography project. He also has collaborators across the world, particularly those in the Pan Prostate Cancer Group, where he leads the Subtypes and Prognostic Signatures working group. Although his primary focus remains prostate cancer, he is open to investigating any cancer type and has ongoing projects in bladder, kidney, colorectal, endometrial and oesophageal cancers.
Recent publications
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Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures.
Journal article
Figiel S. et al, (2023), Mol Cancer, 22
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Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multi-region whole genome sequencing with histopathological features
Preprint
Rao SR. et al, (2023)
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Spatially resolved clonal copy number alterations in benign and malignant tissue.
Journal article
Erickson A. et al, (2022), Nature, 608, 360 - 367
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Prostate cancer evolution from multilineage primary to single lineage metastases with implications for liquid biopsy.
Journal article
Woodcock DJ. et al, (2020), Nat Commun, 11
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Genomic copy number predicts oesophageal cancer years before transformation
Journal article
Killcoyne S. et al, (2020)