Search Results for author:
Found 2 papers, 0 papers with code
Improving PTM Site Prediction by Coupling of Multi-Granularity Structure and Multi-Scale Sequence Representation
Specifically, multigranularity structure-aware representation learning is designed to learn neighborhood structure representations at the amino acid, atom, and whole protein granularity from AlphaFold predicted structures, followed by utilizing contrastive learning to optimize the structure representations. Additionally, multi-scale sequence representation learning is used to extract context sequence information, and motif generated by aligning all context sequences of PTM sites assists the prediction.
ADMEOOD: Out-of-Distribution Benchmark for Drug Property Prediction
On the other hand, CCD describes the data which has inconsistent label among the original data.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
