Novel statistical methods for the design and analysis of proteomic experiments for biomarker discovery

用于设计和分析生物标志物发现的蛋白质组学实验的新统计方法

• 批准号: G0802416/1
• 负责人: David Cairns
• 金额: $ 41.26万
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2009
• 资助国家: 英国
• 起止时间: 2009 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=G0802416%2F1
• 关键词: Novel; statistical; methods; design; analysis

There is an urgent need for new medical tests which can be used to diagnose a disease or to determine how severe a disease is. Such tests can result in earlier and better treatment, increase the chance of recovery and help select the best treatment. A lot of medical research is looking in body fluids such as blood and urine to find proteins (one of the key type of molecules which make up cells and tissues of the body) which could act as markers of disease and be measured in a simple test. Such research uses quite complex technologies and produces very large amounts of data and the purpose of this proposal is to develop the best methods of statistical analysis for this type of data. This is essential so that we reach the right conclusions about whether a marker is a good or bad one.

迫切需要新的医学测试，可以用来诊断疾病或确定疾病的严重程度。这样的测试可以导致更早和更好的治疗，增加康复的机会，并帮助选择最佳治疗。许多医学研究都在寻找血液和尿液等体液中的蛋白质(构成人体细胞和组织的关键分子之一)，这些蛋白质可以作为疾病的标志，并可以通过简单的测试进行测量。这种研究使用了相当复杂的技术，产生了非常大量的数据，这项提议的目的是为这类数据制定最好的统计分析方法。这是至关重要的，这样我们才能就一个标记是好是坏得出正确的结论。