BIOSTATISTICAL COMPUTING RESOURCE

功能强大的计算机工作站正在显著改进生物统计学 现代生物统计学方法在医学中的研究与应用 有问题。本方案是一个应用程序，可以获得集中的数据 文件服务器和CPU，卫星工作站网络，相关联 外围设备和软件，使调查人员能够 交互式访问最先进的统计计算工具和 高分辨率图形。建议的客户端/服务器模型 资源将允许执行计算密集型任务， 将使研究人员能够充分了解络合物的性质 统计模型应用于重要的临床问题。更新的 拟议设备支持的交互式数据分析方法 将提高工作效率，并为无数 小灵通资助的项目。该系统将是一个共享资源，为 满足多个医学部和科室的需求。 一些可能由拟议的 网络适用于患者存活率的统计建模，准确 非参数测试、阿尔茨海默病、临床提前终止 试验，稳健但计算机密集的自举估计，癌症 建模，治疗时机对冠心病的影响，DNA和 蛋白质测序，研究结果和治疗的可变性 大型医学数据库，研究。行为风险因素， 药物动力学模型、心功能和随机模型 心律失常。这些项目与汽车直接相关- 心血管疾病，失能老年患者的危重疾病， 镰状细胞疾病，神经学，癌症，行为医学，以及许多 医学研究的其他领域。 这些项目共享昂贵的资源需求，例如 图形设备、数据存储、能够进行密集计算的CPU、 以及软件开发和维护。可以使用的方法 利用这一资源开发将直接惠及许多领域的研究 重要的医疗问题。

Powerful computer workstations are dramatically improving biostatistical research and the application of modern biostatistical methods to medical problems. This proposal is an application to obtain a centralized data file server and CPU, a network of satellite workstations, associated peripheral devices, and software to allow investigators to have interactive access to state-of-the-art statistical computing tools and high-resolution graphics. The client/server model of the proposed resource will allow computationally intensive tasks to be undertaken that will enable researchers to fully understand the properties of complex statistical models applied to important clinical problems. Newer interactive data analysis methods supported by the proposed equipment will increase productivity and yield better analyses for a myriad of PHS-supported projects. The system would be a shared resource, serving the needs of many medical divisions and departments. Some of the projects that would be made possible by the proposed network pertain to statistical modeling of patient survival, exact nonparametric tests, Alzheimer's disease, early termination of clinical trials, robust but computer-intensive bootstrap estimation, cancer modeling, effects of treatment timing in coronary disease, DNA and protein sequencing, studies of outcome and treatment variability using large medical databases, studies of . behavioral risk factors, pharmacokinetic modeling, cardiac function, and stochastic models of cardiac arrhythmias. These projects are directly related to car- diovascular disease, critical illness in disabled elderly patients, Sickle cell disease, neurology, cancer, behavioral medicine, and many other areas of medical research. These projects share requirements for expensive resources such as graphics devices, data storage, CPUs capable of intensive computations, and software development and maintenance. The methods that can be developed with this resource will directly benefit research in many important medical problems.