Journal
PHYSICS OF LIFE REVIEWS
Volume 2, Issue 1, Pages 65-88Publisher
ELSEVIER
DOI: 10.1016/j.plrev.2005.01.001
Keywords
gene networks; reverse-engineering; machine learning; transcription control; gene regulation
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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. (c) 2005 Elsevier B.V. All rights reserved.
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