Researchers release Hi-TPH dataset and Hi-TPH-PLMs for T cell receptor–pHLA binding prediction
A team led by Zhu, Lu, and colleagues published a new hierarchical dataset called Hi-TPH and a suite of fine-tuned protein language models named Hi-TPH-PLMs in Nature Computational Science. The dataset uses an on-the-fly selection method to generate nonbinding examples, addressing a key limitation in existing tools. On an external wet-lab test set, the models achieve a 19.2% performance gain…
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Key points
- Hi-TPH dataset and Hi-TPH-PLMs released for TCR–pHLA binding prediction
- Models show 19.2% gain over state-of-the-art on external wet-lab test set
- Data and models publicly available under CC BY-NC 4.0 license
Read the original at Nature Machine Learning primary sourceOpen source ↗
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