SGER: Computational Neuroscience Problems with Application to Microarray Expression Analysis

DBI 9978582；SGER计算神经科学问题及其在微阵列表达分析中的应用拟议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内表示和处理的机制。然后，该项目将检验这一假设，即这个问题类似于使用DNA微阵列研究基因表达模式，以了解可能管理基因表达的潜在调控网络。因此，提出的总体意图是采用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，前提是神经映射的科学问题和使用DNA微阵列了解基因调控网络的问题有一些有趣的相似之处。基本的假设是，这两个系统、基因产物调控和神经活动都受控制网络的支配--更深入地了解神经系统，以及随后对神经系统的计算建模，当应用于基因表达的网络控制类比时，可以提供有价值的见解，并最终为一套新的信息学工具奠定基础，该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.