Reverse engineering and verification of gene networks: Principles, assumptions, and limitations of present methods and future perspectives

被引:50
作者
He, Feng [2 ]
Balling, Rudi [2 ]
Zeng, An-Ping [1 ,2 ]
机构
[1] Hamburg Univ Technol, Inst Bioproc & Biosyst Engn, D-21073 Hamburg, Germany
[2] Helmholtz Ctr Infect Res, D-38124 Braunschweig, Germany
关键词
Reverse engineering; Systems biology; Pair wise functional association linkage; Time series expression dynamics; Gene network; Optimal experimental design; TRANSCRIPTIONAL REGULATORY NETWORKS; SINGULAR-VALUE DECOMPOSITION; DYNAMIC BAYESIAN NETWORKS; EXPRESSION DATA; POSTTRANSLATIONAL MODIFICATIONS; SACCHAROMYCES-CEREVISIAE; COMBINATORIAL REGULATION; COEXPRESSION NETWORK; CELLULAR NETWORKS; RNA EXPRESSION;
D O I
10.1016/j.jbiotec.2009.07.013
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Reverse engineering of gene networks aims at revealing the structure of the gene regulation network in a biological system by reasoning backward directly from experimental data. Many methods have recently been proposed for reverse engineering of gene networks by using gene transcript expression data measured by microarray. Whereas the potentials of the methods have been well demonstrated, the assumptions and limitations behind them are often not clearly stated or not well understood. In this review, we first briefly explain the principles of the major methods. identify the assumptions behind them and pinpoint the limitations and possible pitfalls in applying them to real biological questions. With regard to applications, we then discuss challenges in the experimental verification of gene networks generated from reverse engineering methods. We further propose an optimal experimental design for allocating sampling schedule and possible strategies for reducing the limitations of some of the current reverse engineering methods. Finally, we examine the perspectives for the development of reverse engineering and urge the need to move from revealing network structure to the dynamics of biological systems. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:190 / 203
页数:14
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