Success of synthetic model

Study provides evidence that characterizing simple gene networks can help elucidate more complex systems

Melissa Lee Phillips
Feb 15, 2006
Researchers studying simple, synthetic gene networks created mathematical models that enabled them to predict more complex network behaviors, providing a proof-of-principle of one of the central tenets of synthetic and systems biology, according to a report in this week?s Nature.?This broad kind of approach that we call a bottom-up approach is in fact feasible,? senior author J. J. Collins of Boston University told The Scientist. He added that other studies have shown that mathematical models can describe simple synthetic network behavior, but no one had yet shown that these models could then be used to predict more complex behaviors.Led by Collins and first author Nicholas Guido, the researchers engineered four different types of simple gene networks in Escherichia coli cultures. Due to differences in transcriptional promoters, adding certain chemicals to the cultures activated transcription of the green fluorescent protein (GFP) gene in one system, but repressed transcription of...

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