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原文連結
論文資訊
- 類型：已發表論文
- 日期：2009
摘要
Background: Understanding the molecular mechanisms plants have evolved to adapt their 生物 activities to a constantly changing environment is an intriguing question and one that requires a systems biology approach. Here we present a 網絡 analysis of 基因組- wide expression data combined with reverse-engineering 網絡 modeling to dissect the transcriptional control of Arabidopsis thaliana. The regulatory 網絡 is inferred by using an assembly of microarray data containing steady-state RNA expression levels from several growth conditions, developmental stages, biotic and abiotic stresses, and a variety of mutant genotypes. Results: We show that the A. thaliana regulatory 網絡 has the characteristic properties of hierarchical 網絡s. We successfully applied our quantitative 網絡 model to predict the full transcr
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