Cross-disciplinary post-doctoral fellow training scheme in quantative biomedicine (XDF) - 8 x 4 year post-docs

定量生物医学跨学科博士后培训计划 (XDF) - 8 x 4 年博士后

• 批准号: MC_UU_00009/2
• 负责人: Eric Latorre Crespo
• 金额: $ 63.8万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Intramural
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MC_UU_00009%2F2
• 关键词: Cross; disciplinary; post; doctoral; fellow

2018 Intake:Dr. Andrew Papanastasiou - final project title: Uncovering the role and regulation of transcriptional variability in the developing eyeDr Chantriolnt-Andreas Kapourani - final project title: Spatial modelling of transcriptomic changes in tissue pathologyDr Mattia Marenda - final project title: Understanding how nuclear meshes of RNA and proteins regulate the structure of transcriptionally related protein complexesDr Ava Khamseh - final project title: Recurrent clonal expansion trajectories and mutational competition in a model of very early oncogenesis2019 Intake:Dr Vanessa Smer Barreto - final project title: Discovery of new senolytics for anticancer therapy via machine learningDr Lyndsay Kerr - final project title: Understanding the Dynamics of DNA Methylation in Cancer Using Mathematical ModelsDr Eric Latorre Crespo - final project title: Time evolution of age-related clonal hematopoiesis – Mathematical modelling and deep learning approaches to uncover disruptive genetic and epigenetic patterns2020 Intake:Dr Didier Devaurs - final project title: TBC

2018年入学：Andrew Papanastasiou博士-最终项目标题：揭示发育中眼睛转录变异的作用和调节Chantriolnt-Andreas Kapourani博士-最终项目标题：组织病理学中转录组变化的空间建模Mattia Marenda博士-最终项目标题：了解RNA和蛋白质的核网格如何调节转录相关蛋白质复合物的结构Ava Khamseh博士-最终项目标题：非常早期肿瘤发生模型中的复发性克隆扩张轨迹和突变竞争2019年入学：Vanessa Smer Barreto博士-最终项目标题：通过机器学习发现抗癌治疗的新senolytics Lyndsay Kerr博士-最终项目标题：使用数学模型了解癌症中DNA甲基化的动力学Eric Latorre Crespo博士-最终项目标题：年龄相关的克隆造血的时间演变-数学建模和深度学习方法，以揭示破坏性的遗传和表观遗传模式2020摄入量：Didier Devaurs博士-最终项目标题：TBC

项目成果

Higher Order Corrections to Spin Correlations in Top Quark Pair Production at the LHC.

• DOI: 10.1103/physrevlett.123.082001
• 发表时间: 2019-01
• 期刊: Physical review letters
• 影响因子: 8.6
• 作者: A. Behring;M. Czakon;A. Mitov;R. Poncelet;A. Papanastasiou

Machine learning determination of dynamical parameters: The Ising model case

• DOI: 10.1103/physrevb.100.064304
• 发表时间: 2019-08-07
• 期刊: PHYSICAL REVIEW B
• 影响因子: 3.7
• 作者: Cossu, Guido;Del Debbio, Luigi;Wilson, Michael
• 通讯作者: Wilson, Michael

Pervasive lesion segregation shapes cancer genome evolution.

• DOI: 10.1038/s41586-020-2435-1
• 发表时间: 2020-07-01
• 期刊: Nature
• 影响因子: 64.8
• 作者: Aitken, Sarah J;Anderson, Craig J;Taylor, Martin S
• 通讯作者: Taylor, Martin S

3pHLA-score improves structure-based peptide-HLA binding affinity prediction.

• DOI: 10.1038/s41598-022-14526-x
• 发表时间: 2022-06-24
• 期刊: SCIENTIFIC REPORTS
• 影响因子: 4.6
• 作者: Conev, Anja;Devaurs, Didier;Rigo, Mauricio Menegatti;Antunes, Dinler Amaral;Kavraki, Lydia E.
• 通讯作者: Kavraki, Lydia E.

Higher-order interactions in statistical physics and machine learning: A model-independent solution to the inverse problem at equilibrium

统计物理和机器学习中的高阶相互作用：平衡反问题的独立于模型的解决方案

• DOI: 10.48550/arxiv.2006.06010
• 发表时间: 2020
• 作者: Beentjes S