Tag: Computer models
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Understanding the role of cancer’s circular genome in tumour evolution
23rd September 2022
New research, co-led by Dr Benjamin Werner from Barts Cancer Institute at Queen Mary University of London, indicates that the circular DNA structures present in around a third of cancers lead to extensive genetic diversity within tumours, giving them the ability to adapt rapidly to environmental stress and resist targeted cancer treatment.
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Turning back the molecular clock: Tracing cell lineage
6th January 2022
Researchers from Barts Cancer Institute at Queen Mary University of London, the Moffitt Cancer Center and the University of Southern California, have developed a new method that measures subtle changes to the genetic code of cells (called DNA methylation) to study the dynamics of what happens to cells within our bodies over time. The new method, published in Nature Biotechnology, provides a way to measure the birth and death of human cells, making it possible to trace cell lineage and evolution.
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AI algorithm identifies most effective drugs for liver cancer
1st November 2021
Researchers from Barts Cancer Institute at Queen Mary University of London and King’s College Hospital have shown that a new computer-based algorithm can rank drugs used to treat primary liver cancer, based on their efficacy in reducing cancer cell growth.
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OPTIMA: Improving treatment for cancer patients through artificial intelligence
12th October 2021
Professors Claude Chelala and Louise Jones from Barts Cancer Institute, Queen Mary University of London, are part of a €21.3 million public-private research programme that will seek to use artificial intelligence to improve care for patients with prostate, breast and lung cancer.
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BCI researcher receives UKRI Future Leaders Fellowship Award
9th September 2021
Dr Benjamin Werner from Barts Cancer Institute, Queen Mary University of London, is one of the next generation of UK science leaders to receive funding through UK Research and Innovation’s (UKRI) Future Leaders Fellowships scheme. Dr Werner will receive an award of approximately £1.4 million, which will support a research project looking at the evolutionary dynamics of circular extra-chromosomal DNA (ecDNA) in human cancers.
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Dissecting complex biological pathways with machine learning
19th July 2021
We spoke with Group Leader Dr Jun Wang and Postdoctoral Researcher Dr Anthony Anene from Barts Cancer Institute’s Centre for Cancer Genomics & Computational Biology about their most recent publication. Published in Patterns, the paper describes the development of a machine-learning tool called ACSNI that can be used to predict tissue-specific pathway components from large biological datasets.
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