ALSEBO
Active Learning Sequence Exploration via Bayesian Optimization
ALSEBO is a Python framework for navigating protein sequence space using a closed-loop active learning strategy. A Variational Autoencoder (VAE) generates a continuous latent landscape of sequences; Bayesian Optimisation (BO) then iteratively proposes the most promising candidates for experimental testing.
VAE latent landscape
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Sequence Space (DCA · ESM · latent features)
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Initial Training Set (t-SNE / PCA + k-means diversity sampling)
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Experiment → GPR surrogate → UCB acquisition → Next Batch
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active learning loop
Contents
Getting Started
User Guide
Project
API Reference