文档介绍：
基于基因表达谱与 GO 的共调控基因挖掘#
史文丽1,郭茂祖1,李晋1,2,刘晓燕1**
(1. 哈尔滨工业大学计算机科学与技术学院,哈尔滨 150001;
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10
2. 哈尔滨医科大学生物信息科学与技术学院,哈尔滨 150081)
摘要:定义了一种基于子空间搜索的基因表达谱相似度计算方法,首先搜索基因的样本空间,
找出待搜索基因的相关空间,再计算此相关子空间上基因表达水平的相似性,解决了共调控
基因相似性计算中的正反、部分时间和差异表达问题。基因功能分类体系(Gene Ontology)
为基因提供了统一的注释,以一致的、受控的、结构化的术语注释基因的功能,可以用来表
达基因之间的语义功能相似性。本文尝试将表达谱数据与基因本体数据结合起来,并结合图
论中的频繁稠密点集问题,融合信息来构建基因的调控网络,并从中挖掘共调控基因。结果
表明此方法具有很好的应用潜力,融合数据可以为构建基因调控网络提供有价值的信息。
关键词:生物信息学;基因表达数据;相似性度量;语义相似;共调控基因
中图分类号:TP18
15
Co-regulated Gene Mining based on Gene Expression
Profiles and GO
Shi Wenli1, Guo Maozu1, LI Jin1,2, LIU Xiaoyan1
(1. Harbin Institute of Technology, Harbin 150001;
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25
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2. College of Bioinformatics Science and Technology, Harbin Medical University,
Harbin 150081)
Abstract: In this paper we propose a new similarity measure based on subspace firstly
searches for the spatial correlation of the gene, and then calculate the similarity of the gene
expression levels in the sub- can better reflect the spatial information of gene
function classification system (Gene Ontology) provides a unified annotation for
the genes,it is a controlled vocabulary used to describe molecular function, biological process and
ponent of genes and gene products in a generic cell. The study on gene regulatory
networks is a hot topic problem on functional genomics;they plicated life phenomena
from the regulating mechanism among researching of gene works,the
thesis attempted to use both gene expression profiles and GO annotation information to
construct the gene works, then use works mining co-regulated
results show that this method has a good potential application, the integration of information can
provide valuable information for constructing gene work.
Keywords: bioinformatics; gene expression profiles; similarity; semantic similarity;Co-regulated
gene
0 引言
21 世纪是生物技术主宰的世纪,是生命科学和信息技术的世纪。新型 DNA 微阵列技术
已经能够同时监测出数千条基因的表达水平,这项技术使我们在细胞处于