MICA: UK MEDical BIOinformatics partnership - aggregation, integration, visualisation and analysis of large, complex data (UK MED-BIO).

该提案汇集了来自伦敦帝国理工学院（ICL，领导机构）及其合作伙伴的医学、化学、代谢、统计和计算科学领域的一组领先的多学科团队。其中包括癌症研究所、欧洲分子生物学实验室-欧洲生物信息学研究所、牛津大学、斯旺西大学和诺丁汉大学，以及MRC临床科学中心和MRC人类营养研究中心，这些中心得到了与行业、NHS和国家卫生研究所资助的生物医学研究中心和单位的强有力的伙伴关系和合作关系的支持。该提案寻求支持建立一个专门的基础设施，用于数据存储、聚合、分析和可视化不同类型的生物医学数据。这些信息来自标准的临床来源，以及不同类型的信息，包括遗传分析和代谢信息，这些信息帮助我们使用整体“系统医学”框架来定义患者或在一般人群中研究的人群。全球目标是在了解癌症、心血管疾病、呼吸系统疾病和2型糖尿病和肥胖等代谢紊乱等常见人类疾病的病因和进展原因方面取得重大进展。通过这种方式，我们的目标是通过具有强大计算能力的医学生物信息学创新，创造针对个体患者的新的疾病诊断和预后（“分层医学”）。该方案将创造前所未有的能力：1)开发强大的新方法，用于计算和分析大规模、复杂、多来源的医疗数据；（二）整合将血液和尿液样本分析（例如代谢、基因组、微生物基因组分析）等多种不同类型的生物信息与不同疾病、疾病进展和结果联系起来的信息；因此，iii)帮助了解疾病的原因和机制，并改善个别疾病分类，以更好地治疗患者和提高安全性；iv)通过创建跨越生物医学、物理科学、计算机和工程的无缝跨学科环境，转变对未来生物医学研究人员的培训。特别是，我们将利用计算机专业知识，这导致了大学和制药行业之间在医疗信息基础设施和服务方面的合作伙伴关系的发展，称为eTRIKS，以及相关的软件平台，如tranSMART，这是一个用于管理临床研究中的数据和研究知识的“开源”解决方案。我们在代谢“指纹”和系统医学方法方面也拥有世界领先的专业知识，这在位于ICL的MRC-NIHR国家表型中心得到了体现，并以卓越的基因组学、计算科学和先进的数据建模和可视化为基础。该项目与工业部门有非常广泛的合作，包括主要的制药公司、仪器供应商、IT和信息公司。我们的项目涵盖了从基础测量科学水平到基因-环境相互作用和疾病机制的理解，再到基于个体患者生物学的详细知识为更好的临床决策创建知识系统的完整医疗保健数据生成活动和分析。ICL决定在新的帝国西校区建立一个主要的“大数据”跨学科中心，以确保长期的可持续性，从而加强了这一应用。该项目旨在提供一流的科学，强大的信息学平台和深入的科学数据和知识，为英国和国际医学研究的最新技术做出贡献。

This proposal brings together a group of leading multidisciplinary teams in medical, chemical, metabolic, statistical and computational sciences from across Imperial College London (ICL, lead institution) and its partners. These include the Institute of Cancer Research, the European Molecular Biology Laboratory-European Bioinformatics Institute, the Universities of Oxford, Swansea and Nottingham, and the MRC Clinical Sciences Centre and MRC Human Nutrition Research Centre, supported by strong partnerships and collaborative links with industry, the NHS and the National Institute for Health Research funded Biomedical Research Centres and Units. The proposal seeks support to build a DEDICATED INFRASTRUCTURE in data storage, aggregation, analysis and visualisation of diverse types of biomedical data. These come from standard clinical sources through to different types of information including from genetic analysis, and metabolic information, that help us to define patients or people studied in the general population using a holistic "systems medicine" framework. The GLOBAL AIM is to make major advances in understanding the causes and reasons for disease progression of common human diseases such as cancer, cardiovascular disease, respiratory disease and metabolic disorders such as type 2 diabetes and obesity. In this way we aim to create new disease diagnostics and prognostics aimed at the individual patient ("stratified medicine") through innovations in medical bioinformatics with powerful computing capability. The programme will create unprecedented capacity to i) DEVELOP powerful new approaches for computation and analysis of large-scale, complex, multi-source medical data; ii) INTEGRATE information linking multiple different types of biological information from analysis of blood and urine samples (e.g., metabolic, genomic, analysis of the microbial genome) to different diseases, disease progression and outcomes; hence to iii) help UNDERSTAND the causes and mechanisms of disease and improve individual disease classification for better patient treatments and safety; also to iv) TRANSFORM the training of the biomedical researchers of the future through creation of a seamless interdisciplinary environment spanning biomedicine, physical sciences, computing and engineering. In particular we will capitalise on computational expertise that has led to the development of a partnership in medical information infrastructure and service between universities and the pharmaceutical industry called eTRIKS, and related software platforms such as tranSMART, an "open source" solution for managing data and research knowledge in clinical studies. We also have world-leading expertise in metabolic "fingerprinting" and systems medicine approaches manifested in the MRC-NIHR National Phenome Centre located at ICL, and underpinned by excellence in genomics, computational sciences and advanced data modelling and visualisation. This project has a very broad collaboration with industrial sectors including major pharmaceutical companies, instrument vendors, IT and informatics companies. Our project covers the complete healthcare envelope of data generating activity and analysis from the level of basic measurement sciences through to the understanding of gene-environment interactions and disease mechanisms to the creation of knowledge systems for better clinical decision making based on detailed knowledge of individual patient biology. This application is strengthened by the decision of ICL to establish a major interdisciplinary centre for 'big data' at the new Imperial West campus, ensuring sustainability over the longer term. The project aims to deliver top class science, a robust informatics platform and in-depth scientific data and knowledge to contribute to the state of the art of UK and international medical research.