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

目前迫切需要新的医学测试，以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更好的治疗，增加恢复的机会，并帮助选择最佳治疗。许多医学研究都在体液中寻找蛋白质（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，并通过简单的测试进行测量。此类研究使用相当复杂的技术，产生非常大量的数据，本提案的目的是为这类数据开发最佳的统计分析方法。这是至关重要的，这样我们才能得出关于一个标记是好是坏的正确结论。

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.