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‎index.html‎

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@@ -50,18 +50,18 @@ <h3>Engineering biology</h3>
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<section>
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<span class="feature-icon"><a href="#cancer_popup" class="icon solid fa-dna"></a></span>
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<span class="feature-icon"><a href="#microbiome_popup" class="icon solid fa-microscope"></a></span>
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<header>
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<h3>Mutational processes</h3>
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<h3>Microbiome engineering</h3>
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<span class="feature-icon"><a href="#microbiome_popup" class="icon solid fa-microscope"></a></span>
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<span class="feature-icon"><a href="#cancer_popup" class="icon solid fa-dna"></a></span>
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<header>
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<h3>Microbiome engineering</h3>
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<h3>Mutational processes</h3>
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@@ -389,67 +389,6 @@ <h2>Engineering Biology</h2>
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<section id="research_cancer" class="main">
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<header>
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<div class="container">
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<h2>Mutational processes</h2>
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<figure>
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<img width="50%" src="images/science/PDTO-model.jpg" alt="" />
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<figcaption>Fig: Modelling chromosomal gain and loss within a stochastic branching process </figcaption>
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</figure>
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<p> MA al-Badri, WCH Cross, CP Barnes (2024).
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Explainable deep learning on 7500 whole genomes elucidates cancer-specific patterns of chromosomal instability.
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bioRxiv, <a href=https://doi.org/10.1101/2024.03.08.584160> 2024.03.08.584160 </a></p>
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<p> B Lu, S Winnall, W Cross, CP Barnes (2024).
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Cell-cycle dependent DNA repair and replication unifies patterns of chromosome instability.
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bioRxiv, <a href=https://doi.org/10.1101/2024.01.03.574048> 2024.01.03.574048</a></p>
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<p> Lu, B., Curtius, K., Graham, T.A., Yang, Z., Barnes, C.P. (2023).
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CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples.
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Genome biology, 24 doi:<a href=https://genomebiology.biomedcentral.com/articles/10.1186/s13059-023-02983-0>10.1186/s13059-023-02983-0</a></p>
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<p> Gabbutt, C., Schenck, R.O., Weisenberger, D.J., Kimberley, C., Berner, A., Househam, J., ...Patel, R. (2022).
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Fluctuating methylation clocks for cell lineage tracing at high temporal resolution in human tissues.
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Nature Biotechnology, doi:<a href=https://www.nature.com/articles/s41587-021-01109-w>10.1038/s41587-021-01109-w</a></p>
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<p> Bollen, Y., Stelloo, E., van Leenen, P., van den Bos, M., Ponsioen, B., Lu, B., ...Snippert H.J.G. (2021).
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Reconstructing single-cell karyotype alterations in colorectal cancer identifies punctuated and gradual diversification patterns.
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Nature Genetics, doi:<a href=https://www.nature.com/articles/s41588-021-00891-2>10.1038/s41588-021-00891-2</a>
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</p>
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<p> Williams, M.J., Zapata, L., Werner, B., Barnes, C.P., Sottoriva, A., Graham, T.A. (2020).
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Measuring the distribution of fitness effects in somatic evolution by combining clonal dynamics with dN/dS ratios.
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eLife, 9 doi:<a href=https://doi.org/10.7554/eLife.48714>10.7554/eLife.48714</a>
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</p>
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<p>Williams, M.J., Werner, B., Heide, T., Curtis, C., Barnes, C.P., Sottoriva, A., Graham, T.A. (2018).
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Quantification of subclonal selection in cancer from bulk sequencing data.
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Nature Genetics 2018 Jun;50(6):895-903. doi:<a href=https://doi.org/10.1038/s41588-018-0128-6>10.1038/s41588-018-0128-6</a> <br>
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<a href=https://www.thetimes.co.uk/edition/news/tumour-growth-can-be-predicted-by-computer-bdqp5c6ww> Article in The Times </a>
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</p>
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<p>
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Woods M.L., Barnes C.P. (2016).
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Mechanistic Modelling and Bayesian Inference Elucidates the Variable Dynamics of Double-Strand Break Repair.
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PLoS Comput Biol. 2016 Oct 14;12(10):e1005131. doi:<a href=https://doi.org/10.1371/journal.pcbi.1005131>10.1371/journal.pcbi.1005131</a>
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</p>
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<p>
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Williams, M.J., Werner, B, Barnes, C.P., Graham, T.A., & Sottoriva, A. (2016).
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Identification of neutral tumor evolution across cancer types.
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Nature Genetics, 2016 Jan 18. doi:<a href=https://doi.org/10.1038/ng.3489>10.1038/ng.3489</a>
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</p>
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<p>
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Chaidos, A, Barnes, C.P. et. al. (2013).
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Clinical drug resistance linked to interconvertible phenotypic and functional states of tumor-propagating cells in multiple myeloma.
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Blood. 2013 Jan 10;121(2):318-28. doi:<a href=https://doi.org/10.1182/blood-2012-06-436220>10.1182/blood-2012-06-436220</a>
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</p>
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</div>
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</header>
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</section>
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<section id="research_microbiome" class="main">
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<header>
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<div class="container">
@@ -554,6 +493,67 @@ <h2>Microbiome engineering</h2>
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</header>
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</section>
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<section id="research_cancer" class="main">
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<header>
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<div class="container">
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<h2>Mutational processes</h2>
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<figure>
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<img width="50%" src="images/science/PDTO-model.jpg" alt="" />
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<figcaption>Fig: Modelling chromosomal gain and loss within a stochastic branching process </figcaption>
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</figure>
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<p> MA al-Badri, WCH Cross, CP Barnes (2024).
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Explainable deep learning on 7500 whole genomes elucidates cancer-specific patterns of chromosomal instability.
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bioRxiv, <a href=https://doi.org/10.1101/2024.03.08.584160> 2024.03.08.584160 </a></p>
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<p> B Lu, S Winnall, W Cross, CP Barnes (2024).
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Cell-cycle dependent DNA repair and replication unifies patterns of chromosome instability.
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bioRxiv, <a href=https://doi.org/10.1101/2024.01.03.574048> 2024.01.03.574048</a></p>
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<p> Lu, B., Curtius, K., Graham, T.A., Yang, Z., Barnes, C.P. (2023).
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CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples.
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Genome biology, 24 doi:<a href=https://genomebiology.biomedcentral.com/articles/10.1186/s13059-023-02983-0>10.1186/s13059-023-02983-0</a></p>
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<p> Gabbutt, C., Schenck, R.O., Weisenberger, D.J., Kimberley, C., Berner, A., Househam, J., ...Patel, R. (2022).
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Fluctuating methylation clocks for cell lineage tracing at high temporal resolution in human tissues.
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Nature Biotechnology, doi:<a href=https://www.nature.com/articles/s41587-021-01109-w>10.1038/s41587-021-01109-w</a></p>
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<p> Bollen, Y., Stelloo, E., van Leenen, P., van den Bos, M., Ponsioen, B., Lu, B., ...Snippert H.J.G. (2021).
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Reconstructing single-cell karyotype alterations in colorectal cancer identifies punctuated and gradual diversification patterns.
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Nature Genetics, doi:<a href=https://www.nature.com/articles/s41588-021-00891-2>10.1038/s41588-021-00891-2</a>
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</p>
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<p> Williams, M.J., Zapata, L., Werner, B., Barnes, C.P., Sottoriva, A., Graham, T.A. (2020).
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Measuring the distribution of fitness effects in somatic evolution by combining clonal dynamics with dN/dS ratios.
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eLife, 9 doi:<a href=https://doi.org/10.7554/eLife.48714>10.7554/eLife.48714</a>
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</p>
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<p>Williams, M.J., Werner, B., Heide, T., Curtis, C., Barnes, C.P., Sottoriva, A., Graham, T.A. (2018).
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Quantification of subclonal selection in cancer from bulk sequencing data.
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Nature Genetics 2018 Jun;50(6):895-903. doi:<a href=https://doi.org/10.1038/s41588-018-0128-6>10.1038/s41588-018-0128-6</a> <br>
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<a href=https://www.thetimes.co.uk/edition/news/tumour-growth-can-be-predicted-by-computer-bdqp5c6ww> Article in The Times </a>
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</p>
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<p>
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Woods M.L., Barnes C.P. (2016).
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Mechanistic Modelling and Bayesian Inference Elucidates the Variable Dynamics of Double-Strand Break Repair.
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PLoS Comput Biol. 2016 Oct 14;12(10):e1005131. doi:<a href=https://doi.org/10.1371/journal.pcbi.1005131>10.1371/journal.pcbi.1005131</a>
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</p>
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<p>
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Williams, M.J., Werner, B, Barnes, C.P., Graham, T.A., & Sottoriva, A. (2016).
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Identification of neutral tumor evolution across cancer types.
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Nature Genetics, 2016 Jan 18. doi:<a href=https://doi.org/10.1038/ng.3489>10.1038/ng.3489</a>
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</p>
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<p>
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Chaidos, A, Barnes, C.P. et. al. (2013).
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Clinical drug resistance linked to interconvertible phenotypic and functional states of tumor-propagating cells in multiple myeloma.
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Blood. 2013 Jan 10;121(2):318-28. doi:<a href=https://doi.org/10.1182/blood-2012-06-436220>10.1182/blood-2012-06-436220</a>
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</p>
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</div>
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</header>
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</section>
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