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基因调控网络模型构建方法 |
虞慧婷,吴骋,柳伟伟,付旭平,贺佳 |
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(第二军医大学卫生勤务学系卫生统计学教研室,上海,200433;复旦大学遗传学研究所遗传工程重点实验室,上海,200433) |
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摘要: |
基因调控网络的研究从基因之间相互作用的角度揭示复杂的生命现象,是功能基因组学研究的重要内容,也是当前生物信息学研究的前沿.基因芯片技术在生物信息学中的应用为基因调控网络的研究提供大量可供研究与分析的基础数据.本文介绍了基因调控网络的起源与近年来的发展情况,详细说明了基因调控网络构建的前提与基本原理,并分析几种经典调控网络模型:布尔网络模型、线性及非线性模型和贝叶斯网络模型,阐述各种模型构建的基本原理和算法,结合基因芯片的数据特点,探讨各种模型的优缺点及其适用情况,对各种网络模型进行分析与总结. |
关键词: 基因调控网络、布尔网络模型、线性模型、非线性模型、贝叶斯模型 |
DOI:10.3724/SP.J.1008.2006.00737 |
投稿时间:2006-01-19修订日期:2006-05-25 |
基金项目:国家自然科学基金(30471502);上海市自然科学基金(04ZR14049). |
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Modeling of gene regulatory networks |
YU Hui-ting,WU Cheng,LIU Wei-wei,FU Xu-ping,HE Jia |
(第二军医大学卫生勤务学系卫生统计学教研室,上海,200433) |
Abstract: |
Gene regulatory networks (GRN), which focuses on the complex interactions of genes in life, is an important part in the study of the functional genomics and is the frontier of bioinformatics research. Application of gene-chip technique in bioinformatics provides a great number of basic data for the research of GRN. This paper reviews the origin and recent development of GRN, explicates the preconditions and rationales for construction of GRN, and analyzes several classic GRN models: Boolean networks, linear models, non-linear models and Bayesian networks. The rationales, basic algorithms, advantages, disadvantages and applicability of the models are reviewed based on the characteristics of gene-chip data. |
Key words: gene regulatory networks Boolean networks, linear models non-linear models Bayesian networks |