UK Multi-Scale Biology Network

英国多尺度生物学网络

• 批准号: BB/M025888/1
• 负责人: Markus Owen
• 金额: $ 12.94万
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FM025888%2F1
• 关键词: UK; Multi; Scale; Biology; Network

Life, from single cells such as bacteria, to populations of plants and animals is complex and multi-layered. Processes acting at one scale can have profound effects on a system at larger and smaller scales. For example, single bacterial cells, whose size is a fraction of the width of a human hair, can form colonies whose behaviour is massively influenced by their collective interaction. Molecular and physical events at the tip of growing plant roots or shoots can have profound effects on the whole plant, and therefore on food production. Diseases that manifest themselves at the scale of whole organs (e.g. lungs, hearts, livers) often arise due to microscopic changes at the level of the individual cells that make up those organs. Multi-scale biology seeks to improve our understanding of these multi-layered biological systems by developing new approaches that combine biological sciences with other disciplines such as mathematics, physics, computer science and engineering. This means gathering data at multiple relevant scales (e.g. single cell and whole tissue scale; individual plants/animals and farm or ecosystem scale) and developing tools for reasoning about and modelling such systems whilst taking into account how changes at one scale may impact the system at other scales. Multi-scale biology presents many new challenges to the relevant disciplines, and many opportunities to exploit capabilities developed in different contexts. For example, weather forecasting and climate modeling rely on sophisticated computer models and techniques of data analysis which could be adapted for use in the biological context. Experience in those fields demonstrates how important is the availability of large amount of quantitative data defined over space, time, and across scales, and suggests that a major shift is required in the biosciences to make routine the generation of similarly detailed data. On the other hand, many advances have been made in the analysis and computer modelling of multiscale biological systems, but many of the models are hard to re-use or combine with other tools in novel ways. Thus a community effort is required to share best practice, to encourage the development and adoption of standards for sharing data and models, to identify opportunities in the field, and to bring together teams of scientists to address grand challenges in the biosciences, such as global food security, sustainability, healthcare, and the reduction and replacement of animals in research. The proposed network will run community building events (where many scientists from different disciplines give short "pitches" about their work and how it can contribute to multi-scale biology), hackathons and study groups (where teams work together over a week in an intensive way to develop computational tools or models), and a summer school (providing training in multi-scale biology). Furthermore, the network will host a website to facilitate community interactions and resource sharing, and support exchange visits between research groups to help launch new collaborations.

生命，从细菌等单细胞到植物和动物的种群，都是复杂而多层次的。在一个尺度上作用的过程可以在更大和更小的尺度上对系统产生深远的影响。例如，单个细菌细胞，其大小是人类头发宽度的一小部分，可以形成菌落，其行为受到集体相互作用的巨大影响。生长中的植物根或芽尖端的分子和物理事件可以对整个植物产生深远的影响，从而对粮食生产产生影响。在整个器官（例如肺，心脏，肝脏）规模上表现出来的疾病通常是由于构成这些器官的单个细胞水平的微观变化而引起的。多尺度生物学试图通过开发将生物科学与其他学科（如数学、物理学、计算机科学和工程学）联合收割机相结合的新方法来提高我们对这些多层次生物系统的理解。这意味着收集多个相关尺度的数据（例如单细胞和整个组织尺度;个体植物/动物以及农场或生态系统尺度），并开发用于推理和建模此类系统的工具，同时考虑到一个尺度的变化可能如何影响其他尺度的系统。多尺度生物学对相关学科提出了许多新的挑战，并为利用在不同背景下开发的能力提供了许多机会。例如，天气预报和气候建模依赖于复杂的计算机模型和数据分析技术，这些模型和技术可以适用于生物学领域。在这些领域的经验表明，大量的定量数据的空间，时间和跨尺度定义的可用性是多么重要，并表明，在生物科学需要一个重大的转变，使日常的类似详细的数据的生成。另一方面，在多尺度生物系统的分析和计算机建模方面已经取得了许多进展，但是许多模型很难以新的方式重复使用或与其他工具联合收割机结合。因此，需要社区努力分享最佳实践，鼓励制定和采用共享数据和模型的标准，确定该领域的机会，并将科学家团队聚集在一起，以应对生物科学的重大挑战，例如全球粮食安全，可持续性，医疗保健以及减少和替代研究中的动物。拟议中的网络将运行社区建设活动（来自不同学科的许多科学家对他们的工作以及如何为多尺度生物学做出贡献进行简短的“推销”），黑客马拉松和研究小组（团队在一周内以密集的方式共同开发计算工具或模型），以及暑期学校（提供多尺度生物学培训）。此外，该网络将建立一个网站，以促进社区互动和资源共享，并支持研究小组之间的互访，以帮助开展新的合作。

项目成果

OPTiMAL: a new machine learning approach for GDGT-based palaeothermometry

• DOI: 10.5194/cp-2019-60
• 发表时间: 2019-06
• 期刊: Climate of the Past
• 影响因子: 4.3
• 作者: T. Dunkley Jones;Y. Eley;W. Thomson;S. Greene;I. Mandel;K. Edgar;J. Bendle

Influence of microvascular sutures on shear strain rate in realistic pulsatile flow.

• DOI: 10.1016/j.mvr.2018.03.001
• 发表时间: 2018-07
• 期刊: Microvascular research
• 影响因子: 3.1
• 作者: R. Wain;David J. Smith;Doug E. Hammond;J. Whitty

Abnormal morphology biases hematocrit distribution in tumor vasculature and contributes to heterogeneity in tissue oxygenation.

• DOI: 10.1073/pnas.2007770117
• 发表时间: 2020-11-10
• 期刊: Proceedings of the National Academy of Sciences of the United States of America
• 影响因子: 11.1
• 作者: Bernabeu MO;Köry J;Grogan JA;Markelc B;Beardo A;d'Avezac M;Enjalbert R;Kaeppler J;Daly N;Hetherington J;Krüger T;Maini PK;Pitt-Francis JM;Muschel RJ;Alarcón T;Byrne HM
• 通讯作者: Byrne HM

Defining vitamin D status using multi-metabolite mathematical modelling: A pregnancy perspective.

• DOI: 10.1016/j.jsbmb.2019.03.024
• 发表时间: 2019-06
• 期刊: The Journal of steroid biochemistry and molecular biology
• 作者: Beentjes CHL;Taylor-King JP;Bayani A;Davis CN;Dunster JL;Jabbari S;Mirams GR;Jenkinson C;Kilby MD;Hewison M;Tamblyn JA
• 通讯作者: Tamblyn JA

Topology-dependent density optima for efficient simultaneous network exploration

用于高效同步网络探索的拓扑相关密度最佳值

• DOI: 10.48550/arxiv.1709.08706
• 发表时间: 2017
• 作者: Wilson D