High-entropy Boltzmann Machines on protein sequences generate functional artificial enzymes from a viable sequence space more than 15 orders of magnitude larger than low-entropy models while maintaining high success rates in cell-based tests.
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A pairwise maximum-entropy model fitted to Scrabble tile graphs reproduces observed statistics, predicts word-length and geometric features, and classifies languages by entropy and structure.
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Expanding functional protein sequence space using high entropy generative models
High-entropy Boltzmann Machines on protein sequences generate functional artificial enzymes from a viable sequence space more than 15 orders of magnitude larger than low-entropy models while maintaining high success rates in cell-based tests.
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Statistical mechanics for Scrabble predicts strategy, entropy and language
A pairwise maximum-entropy model fitted to Scrabble tile graphs reproduces observed statistics, predicts word-length and geometric features, and classifies languages by entropy and structure.