Reverse-engineering transcription control networks

Timothy S. Gardner, Jeremiah J. Faith

Research output: Contribution to journalReview articlepeer-review

183 Scopus citations


Microarray technologies, which enable the simultaneous measurement of all RNA transcripts in a cell, have spawned the development of algorithms for reverse-engineering transcription control networks. In this article, we classify the algorithms into two general strategies: physical modeling and influence modeling. We discuss the biological and computational principles underlying each strategy, and provide leading examples of each. We also discuss the practical considerations for developing and applying the various methods.

Original languageEnglish
Pages (from-to)65-88
Number of pages24
JournalPhysics of Life Reviews
Issue number1
StatePublished - Mar 2005
Externally publishedYes


  • Gene networks
  • Gene regulation
  • Machine learning
  • Reverse-engineering
  • Transcription control


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