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We present a probabilistic modeling framework and adaptive sampling algorithm wherein unsupervised generative models are combined with black box predictive models to tackle the problem of input design.
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Evaluation of 244,000 synthetic sequences reveals design principles to optimize translation in Escherichia coli
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