Tag: Computer models

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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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BCI researcher part of team shortlisted for Cancer Grand Challenges awards

23rd June 2021

Dr Benjamin Werner from Barts Cancer Institute, Queen Mary University of London, is part of an international team that has been selected to share its ideas on how to solve one of cancer’s toughest challenges.

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