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Black-box optimization formulations for biological sequence design have drawn recent attention due to their promising potential impact on the pharmaceutical industry.
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Enzyme engineering for nonaqueous solvents: Random mutagenesis to enhance activity of subtilisin e in polar organic media
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Rafael Izbicki, Ann B. Lee, and Chad M. Schafer · 2014
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Auto-encoding variational bayes
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Dropout: a simple way to prevent neural networks from overfitting
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Variational bayes with intractable likelihood
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Survey of variation in human transcription factors reveals prevalent dna binding changes
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Anvita Gupta and J. Zou · 2019
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Likelihood-free mcmc with amortized approximate likelihood ratios
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Regularized evolution for image classifier architecture search
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Human 5 utr design and variant effect prediction from a massively parallel translation assay
Paul Sample, Ban Wang, David W. Reid, Vladimir Presnyak, Iain J Mcfadyen, David R. Morris, and Georg Seelig · 2019
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Deep learning regression model for antimicrobial peptide design
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Machine learning-assisted directed protein evolution with combinatorial libraries
Zachary Wu, S B Jennifer Kan, Russell D Lewis, Bruce J. Wittmann, and Frances H. Arnold · 2019
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Antibody complementarity determining region design using high-capacity machine learning
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Graphaf: a flow-based autoregressive model for molecular graph generation
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Error-guided likelihood-free mcmc
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