Using Transformer protein embeddings with a linear attention mechanism to make SOTA de-novo predictions for the subcellular location of proteins 🔬
-
Updated
Sep 6, 2023 - Jupyter Notebook
Using Transformer protein embeddings with a linear attention mechanism to make SOTA de-novo predictions for the subcellular location of proteins 🔬
Deep Critical Learning. Implementation of ProSelfLC, IMAE, DM, etc.
Semi-supervised VAE model for protein localization prediction from microscopy images
An R package that visualizes Human Cell Atlas annotations on an SVG cell image.
Add a description, image, and links to the protein-localization topic page so that developers can more easily learn about it.
To associate your repository with the protein-localization topic, visit your repo's landing page and select "manage topics."