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Cell. 2007 Dec 28;131(7):1354-65.

A predictive model for transcriptional control of physiology in a free living cell.

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Center for Genomics & Systems Biology, New York University, New York, NY 10003, USA; Courant Institute of Mathematical Sciences, Department of Computer Science, New York University, New York, NY 10003, USA.


The environment significantly influences the dynamic expression and assembly of all components encoded in the genome of an organism into functional biological networks. We have constructed a model for this process in Halobacterium salinarum NRC-1 through the data-driven discovery of regulatory and functional interrelationships among approximately 80% of its genes and key abiotic factors in its hypersaline environment. Using relative changes in 72 transcription factors and 9 environmental factors (EFs) this model accurately predicts dynamic transcriptional responses of all these genes in 147 newly collected experiments representing completely novel genetic backgrounds and environments-suggesting a remarkable degree of network completeness. Using this model we have constructed and tested hypotheses critical to this organism's interaction with its changing hypersaline environment. This study supports the claim that the high degree of connectivity within biological and EF networks will enable the construction of similar models for any organism from relatively modest numbers of experiments.

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