SGER: Computational Neuroscience Problems with Application to Microarray Expression Analysis

DBI 9978582;SGER计算神经科学问题与微阵列表达分析的应用该研究的目标是开发和实施计算方法，以确定信息在神经系统中表示和处理的机制。然后，该项目将检验一个假设，即这个问题类似于使用DNA微阵列研究基因表达模式，以了解可能控制基因表达的潜在调节网络。因此，提出的总体意图是适应神经领域发展的方法来分析来自微阵列实验的基因表达数据。前提是神经图谱的科学问题和使用DNA微阵列来理解基因调控网络的问题有一些有趣的相似之处。潜在的假设是，这两个系统，基因产物调控和神经活动都是由控制网络控制的——当应用于基因表达的网络控制类比时，更深入的理解和随后的神经系统计算建模可以提供有价值的见解，并最终为一套新的信息学工具提供基础，这些工具旨在更好地分析微阵列基因表达数据。

DBI 9978582; SGER Computational Neuroscience Problems with application to Microarray Expression AnalysisThe objective of the proposed research is to develop and implement computationalapproaches for determining the mechanisms through which information is representedand processed within neural systems. The project will then examine the hypothesis that this problem is similar to studying gene expression patterns using DNA microarrays in order to learn about the underlying regulatory networks that presumably govern gene expression. Thus, the proposed overall intent is to adapt methods developed in the neural domain to analyze gene expression data from microarray experiments.The premise is that the scientific problem of neural mapping and the problem of using DNA microarrays to understand gene regulatory networks share some interesting similarities. The underlying assumption is that both systems, gene product regulation and neural activity are governed by a control network-understanding in greater depth and subsequent computational modeling of the neural system could, when applied to the network control analogy in gene expression provide valuable insights and ultimately the basis of a new set of informatics tools designed to better analyze microarray gene expression data.