Stochastic Differential Equations
Differential equations that combine deterministic evolution with random forcing to represent systems influenced by continuous uncertainty.
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Protein Language Models
Machine-learning models that learn statistical representations of amino-acid sequences for prediction and molecular design.
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Optimal Transport
A mathematical framework for transforming one distribution into another while minimising a defined movement cost.
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Computational Protein Design
The algorithmic creation of amino-acid sequences expected to fold into structures with specified biochemical functions.
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Artificial Neural Networks
Layered computational models that learn distributed representations by adjusting weighted connections from data.
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