Cellular networks interact to result in the organismal phenotype, yet these networks have so far been difficult to integrate. Chandrasekaran and Price have developed an approach — Gene Expression and Metabolism Integrated for Network Interference (GEMINI) — that is able to constrain predicted gene regulatory networks on the basis of metabolic data in yeast. They used GEMINI to build a network in Saccharomyces cerevisiae and used it to predict phenotypes such as growth effects after transcription factor knockout in new conditions. This will be a valuable tool in synthetic biology.
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11 February 2014
In this In Brief, the incorrect journal was listed in the citation. The citation should have been: Chandrasekaran, S. & Price, N. D. Metabolic constraint-based refinement of transcriptional regulatory networks. PLoS Comput. Biol. 9, e1003370 (2013). The article has been corrected online. The editors apologize for this error.
References
Chandrasekaran, S. & Price, N. D. Metabolic constraint-based refinement of transcriptional regulatory networks. PLoS Comput. Biol. 9, e1003370 (2013)
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Stower, H. Metabolically constrained regulatory networks. Nat Rev Genet 15, 65 (2014). https://doi.org/10.1038/nrg3665
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DOI: https://doi.org/10.1038/nrg3665