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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.

为了构建具有计算生命的遗传调控网络，已经进行了以下系统和算法的开发。一种用于探索基因序列之间的共同保守区域的系统。给定功能彼此相同或相似的基因序列家族，我们已经开发了用于鉴定序列之间保守的序列模式的系统。我们的系统检测这样的模式：构建一个图，其顶点是每一个可能的固定长度的区域的序列，其边缘绘制，如果任何两个区域的相似性超过一个给定的截止;并提取一个最大密度的子图中的图形。通过对大肠杆菌双组分系统、转录调控基因家族、头休克蛋白等已知保守区域的分析，验证了该系统的有效性.利用基因表达谱的基因聚类系统。DNA芯片技术已广泛应用于基因表达分析。然而，实验噪声阻碍了表达数据的有效利用。为了科普这个问题，我们开发了一个系统，通过傅立叶变换和小波变换将时间序列表达数据转换到频域，并去除信号的高频分量，从而减少这种噪声。3.代谢途径的多重比对算法。代谢途径已被公认为最知名的分子网络之一。我们已经开发了一种算法，通过比较EC数所代表的反应序列来找到几种途径之间的共同保守的反应模式。我们的算法的有效性证明，通过寻找保守的糖代谢途径之间的反应和氨基酸的生物合成途径之间。