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

Paper ID Volume ID Publish Year Pages File Format Full-Text
24112 43498 2009 14 PDF Available
Title
Reverse engineering and verification of gene networks: Principles, assumptions, and limitations of present methods and future perspectives
Abstract

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.

Keywords
Reverse engineering; Systems biology; Pair wise functional association linkage; Time series expression dynamics; Gene network; Optimal experimental design
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Publisher
Database: Elsevier - ScienceDirect
Journal: Journal of Biotechnology - Volume 144, Issue 3, November 2009, Pages 190–203
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us