STATISTICAL PHYSICS APPROACH TO PATTERN ANALYSIS OF GENE CHIP DATA

这个子项目是利用由NIH/NCRR资助的中心拨款提供的资源的许多研究子项目之一。子项目和调查员(PI)可能从另一个NIH来源获得了主要资金，因此可能会出现在其他CRISE条目中。列出的机构是针对中心的，而不一定是针对调查员的机构。心律失常的发生往往与心脏冲动传导的改变有关。反过来，这种特性可能与负责膜电位的离子通道的动态变化有关。为了了解细胞行为和心律失常之间的联系，我们正在研究小鼠选定离子通道基因表达水平的变化。与蒙特利尔心脏研究所的特里·赫伯特博士合作，我们正在分析来自微阵列实验的基因表达数据。这些数据噪音很大，人们对噪音的系统性来源知之甚少。我们的目标是首先从数据集中提取可靠的信息，然后使我们能够研究不同病理条件下离子通道的表达。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Arrhythmogenesis is often related to changes in cardiac impulse conduction. This property, in turn, may be related to altered dynamics of the ion channels responsible for the membrane potential. To understand the connection between the cellular behavior and cardiac arrhythmias, we are investigating alterations in the gene expression levels of selected ion channels in mice. In collaboration with Dr. Terry Hebert, Montreal Heart Institute, we are analyzing gene expression data from micro-array experiments. The data are very noisy, and little is known about the systematic origins of the noise. Our goal is first to extract reliable information from the datasets which will then enable us to study the expression of ion channels under different pathologic conditions.