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

Feng He, Rudi Balling, An Ping Zeng*

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

61 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)190-203
Number of pages14
JournalJournal of Biotechnology
Volume144
Issue number3
DOIs
Publication statusPublished - Nov 2009
Externally publishedYes

Keywords

  • Gene network
  • Optimal experimental design
  • Pair wise functional association linkage
  • Reverse engineering
  • Systems biology
  • Time series expression dynamics

Fingerprint

Dive into the research topics of 'Reverse engineering and verification of gene networks: Principles, assumptions, and limitations of present methods and future perspectives'. Together they form a unique fingerprint.

Cite this