Integrated Bioinformatic Analysis of Genomic Datasets

说明： 这个应用程序的两个目标是支持我作为临床和生物医学信息学家的培训，以及开发和利用软件应用程序，这些应用程序将执行对具有临床数据和基因注释的功能基因组数据集的集成分析。该奖项将通过在华盛顿大学遗传学教授加里·斯托莫博士的指导下提供生物信息学培训，促进我向独立研究人员的转变。斯托尔莫博士非常适合作为我的导师，因为他的实验室在开发和使用计算生物学和生物信息学工具方面拥有丰富的经验，而且他已经拥有促进成功完成这项申请的所有资源。他还通过为过去的研究生涯奖获得者担任导师，展示了他成为一名好导师的能力。计算生物学的教学计划将补充斯托尔莫博士的实验室提供的知识环境，与该项目的其他合作者举行的会议，以及生物信息学领域的国家会议。 生物医学研究的目标是发现导致疾病状态的重要途径中的扰动，以便设计治疗方法。很明显，大多数疾病是由遗传程序的一个或多个水平的改变引起的。只有同时监测DNA、RNA和蛋白质，才能全面了解多因素疾病发生的潜在过程。虽然非常需要分析从这种全基因组图谱实验获得的数据与从临床数据确定的数据，但没有软件应用程序可以有效地执行这一任务。这项建议的具体目标是开发一种新的应用程序，使用先进的统计算法同时分析和可视化具有临床病理患者数据和基因注释的功能基因组数据集，并利用该软件分析正在进行的两项髓系白血病和前列腺癌研究的数据。这种组合分析将有助于识别以前被低估的途径和 分子标记，可用于设计诊断分析和定制治疗。

DESCRIPTION: The two objectives of this application are to support my training as a clinical and biomedical informatician and to develop and utilize software applications that will perform integrated analyses of functional genomic datasets with clinical data and gene annotation. This award will facilitate my transition into an independent investigator by providing bioinformatics training under the mentorship of Dr. Gary Stormo, Professor of Genetics at Washington University. Dr. Stormo is ideally suited to be my mentor because his laboratory has extensive experience in developing and using computational biology and bioinformatics tools and because he has all the resources already in place to facilitate the successful completion of this application. He has also demonstrated the ability to be a good mentor by serving as one to past research career award recipients. A didactic program in computational biology will complement the intellectual environment provided by Dr. Stormo's laboratory, the meetings with other collaborators on this project, and national conferences in the field of bioinformatics. The goal of biomedical research is to uncover perturbations in important pathways that lead to disease states so that therapeutic treatments may be designed. It is clear that most diseases are caused by alterations at one or more levels of the genetic program. Only through simultaneous monitoring of DMA, RNA, and protein can the comprehensive understanding of underlying processes occurring in multi-factorial diseases be made. While there is a great need to analyze data derived from such genome-wide profiling experiments with that ascertained from clinical data simultaneously, there are no software applications which can effectively perform this task. The specific aims of this proposal are to develop a novel application to concurrently analyze and visualize functional genomic datasets with clinicopathology patient data and gene annotation using advanced statistical algorithms and to utilize this software to analyze data from two ongoing studies in myeloid leukemia and prostate cancer. Such combinatorial analyses will facilitate the identification of previously underappreciated pathways and molecular markers which may be used to design diagnostic assays and customized therapies.