AlphaFold Decoded: Feature Embedding (Lesson 6)

In the sixth video of this series, we explore Feature Embedding, a key aspect of AlphaFold’s input processing. You’ll delve into the workings of AlphaFold’s input embedder, the recycling embedder, and the ExtraMSA Stack. These modules are essential for preparing and refining the input data before it reaches the Evoformer, ensuring that the model has a comprehensive understanding of the protein’s context and evolutionary information.
In the Jupyter Notebook, you’ll implement these embedding modules step-by-step, gaining practical insights into how they contribute to AlphaFold’s overall structure prediction process.
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Timestamps:
0:00 Intro
1:44 Input Embedder
3:14 Recycling Embedder
6:38 Extra MSA Stack
9:44 Outro