Semiparametric Models for Large Scale-Biomedical Data

这一建议的目的是发展新的统计方法，以解决分析大型 从生物医学研究，特别是肿瘤和病毒性疾病的研究的规模数据。的问题 从DMA微阵列分析中产生的蛋白质组学和纵向数据将被仔细研究。 该提案的重点是开发创新的半参数技术，以消除系统性偏倚， 微阵列实验，选择在不同时间显著表达的基因和蛋白质 点和不同的实验条件下，有效地评估协变量的影响， 预测纵向研究的个体反应轨迹。每个人的长处和短处 所提出的方法将严格审查通过理论研究和模拟研究。相关 将开发软件。正在进行的癌症和病毒性疾病生物学研究的数据集将被 使用新开发的统计方法进行分析。这项研究使生物学家能够更有效地 消除了微阵列实验中遗传的实验变异的影响，并允许生物学家 以更低的错误发现率揭示更有意义的科学结果。它提供了尖端的工具， 生物学家了解生物过程，分子功能和细胞活动。它介绍了新的 医学科学家的工具，揭示风险因素如何随着时间的推移影响个体疾病。这些将导致 在改进疾病分类、诊断、预后和药物设计中， 治疗和医疗目标。

This.aim of this proposal is to develop novel statistical methodology to address issues in the analysis of large scale data from biomedical studies, especially the studies of tumors and virus diseases. The problems arising from the analysis of DMAmicorarray, proteiomic and longitudinal data will be carefully investigated. The proposal focuses on developing innovative semiparametric technqiues for removing systematic biases in microarray experiments, selecting significantly expressed patterns of genes and proteins at different time points and under different experimental conditions, and efficiently assessing the covariate effects and predicting individual response trajectory for longitudinal studies. The strength and weakness of each proposed method will be critically scrutinized via theoretical investigations and simulation studies. Related software will be developed. Data sets from ongoing biologial studies on cancer and virus diseases will be analyzed by using the newly developed statistical methods. This study allows biologists to more effectively remove the impact of experimental variations inherited in microarray experiments and permits biologists to reveal more meaningful scientific results with lower false discovery rates. It provides cutting-edge tools for biologists to understand biological processes, molecular functions and cellular activities. It introduces new tools for medical scientists to unveil how the risk factors affect individual disease over time . These will result in improved disease classification, diagnosis, prognosis, and drug design, among other pharmaceutical, theraputic and medical goals.