NEW INDEXING SCHEME FOR GENE EXPRESSION MICROARRAY DATA

基因组表达数据的微阵列分析是一项新兴技术，它允许生物学家在一次测量中测量单个基因组的大部分基因表达模式。该技术目前正处于商业化的过程中，预计采用该技术的组织将积累大量微阵列分析结果的数据库。微阵列数据非常高的维数意味着现有的数据库索引方案不太适合为大型微阵列数据数据库提供高效的基于内容的搜索。这里提出的工作将开发一种新的数据库索引方案，专门为微阵列数据库的有效搜索而设计。该设计的创新之处在于将特征映射（feature map）和索引（index）相结合，前者将高维数据空间映射到低维特征空间上，后者使用二叉空间划分树来组织特征空间的几何结构。AIMS已经成功地将类似的方法应用于涉及包含来自雷达脉冲的高维信号数据的数据库的索引问题。为这些应用程序开发的软件将构成实现微阵列索引的软件的基础。为了研究所提出的索引方案的性能，将开发一个使用代谢网络的模型，该模型将被设计成产生具有与实际实验数据相似的统计特征的合成微阵列数据。拟议的商业应用：这项研究将提供一个基本的数据库组件，将增加组织中基因组表达微阵列测定的大型数据库的实用性。目前还没有好的替代技术。任何公司希望开发一个系统，将有效地查询信息内容在大型微阵列数据库将需要一个索引方案，如这里提出的一个。

Micro array analysis of genome expression data is an emerging technology that allows biologists to measure patterns of gene expression across a large portion of a single genome in one measurement. The technology is currently in the process of commercialization, and it is expected that organizations that adopt the technology will accumulate large databases of results of micro array analyses. The very high dimensionality of micro array data means that existing data base indexing schemes are not well suited to the problem of providing efficient content based searches of large data bases of microarray data. The work proposed here will develop a new database indexing scheme that is specifically designed for efficient searches of microarray databases. The innovative feature of the design is the combination of a feature map, which maps the very high dimensional data space onto an feature space of lower dimensionality, and an index on the lower dimensional feature space that uses a binary space partition tree to organize the geometry of the feature space. AIMS has successfully applied a similar methodology to indexing problems involving data bases containing high dimensional signal data from radar pulses. The software that was developed for these applications would form the basis for the software that would be implement the micro array index. To investigate the performance of the proposed indexing scheme a model using metabolic networks will be developed which will be designed so as to produce synthetic micro array data with statistical characteristics similar to those of actual experimental data. PROPOSED COMMERCIAL APPLICATIONS: This research will provide a fundamental database component that will increase the usefulness of large databases of micro array assays of genome expression in tissue. No good alternative technologies currently exist. Any company wishing to develop a system that will efficiently query the information content in large microarray databases will require an indexing scheme such as the one proposed here.