Construction of Genetic Regulatory Network with Computational Life

具有计算生命的遗传调控网络的构建

基本信息

批准号：
11680388
负责人：
MATSUDA Hideo
金额：
$ 2.3万
依托单位：
Osaka University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1999
资助国家：
日本
起止时间：
1999 至 2000
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-11680388/
关键词：
genetic sequence analysis gene classification DNA chip gene expression pattern metabolic pathway multiple alignment Bioinformatics

项目摘要

Development of the following systems and algorithms have been carried out for the construction of genetic regulatory network with computational life.1. A system for exploring commonly conserved regions between gene sequences. Given a family of gene sequences of which function is the same as or similar to each other, we have developed a system for identifying sequence patterns that are conserved between the sequences. Our system detects such patterns by : construct a graph whose vertices are every possible fixed-length regions of the sequences, and whose edges are drawn if any two of regions have similarity more than a given cutoff ; and extract a maximum density subgraph in the graph. The effectiveness of our system is demonstrated by examining known conserved regions, such as Escherichia coli two-component systems, transcription regulation gene family, and head shock proteins.2. A clustering system of genes using gene expression profile. DNA chip technology has been widely used for gene expression analyses. The experimental noises, however, hindered the effective use of the expression data. To cope with this issue, we have developed a system for reducing such noises by transforming time-series expression data into the frequency domain by the Fourier and the wavelet transformations and removing the high-frequency components of the signals.3. A multiple alignment algorithm of metabolic pathways. Metabolic pathways have been recognized as one of the most well-known molecular networks. We have developed an algorithm for finding commonly-conserved reaction patterns between several pathways by comparing sequences of reactions represented by the EC numbers. The effectiveness of our algorithms is demonstrated by finding conserved reactions between sugar metabolism pathways and those between amino acid biosynthesis pathways.

已经开发以下系统和算法，以构建具有计算寿命的遗传调节网络1。一个用于探索基因序列之间通常保守区域的系统。给定一个函数的基因序列家族与彼此相同或相似，我们开发了一个系统来识别序列之间保守的序列模式。我们的系统通过：构造一个图形，其顶点是序列的每个可能的固定长度区域，并且如果任何两个区域的相似性大于给定的截止，则绘制边缘的每个模式；并在图中提取最大密度子图。通过检查已知的保守区域，例如大肠杆菌两组分组，转录调控基因家族和头部休克蛋白，可以证明我们系统的有效性。2。使用基因表达谱的基因聚类系统。 DNA芯片技术已被广泛用于基因表达分析。但是，实验噪声阻碍了表达数据的有效使用。为了应对这个问题，我们开发了一个系统来通过将时间序列的表达数据转换为傅立叶和小波变换，并删除信号的高频组件3。代谢途径的多个比对算法。代谢途径已被认为是最著名的分子网络之一。我们开发了一种算法，用于通过比较以EC数为代表的反应序列在几个途径之间找到普遍保存的反应模式。通过发现糖代谢途径与氨基酸生物合成途径之间的保守反应来证明我们算法的有效性。