Published June 6, 2024
| Version v1.2.0
Data paper
Open
AsEP: Benchmarking Deep Learning Methods for Antibody-specific Epitope Prediction
Creators
-
1.
University College London
Description
AsEP is a protein structure dataset that includes 1723 filtered antibody-antigen complexes from abYbank/AbDb.
It is designed to facilitate the development of machine-learning-based models for predicting antibody-specific epitopes given a pair of antibody and antigen structures as input, which is important for antibody engineering. The dataset also introduces a new task for predicting the interacting residue pairs between antibodies and antigens, which is useful for understanding the functional properties of antibodies and enhances the interpretability of model performance.
Please refer to this GitHub repository AsEP-dataset for the dataset interface, which is built with Python and PyTorch-Geometric Dataset Module.
The performance of representative methods for this task is also provided.
Files
README.md
Files
(12.5 GB)
| Name | Size | Download all |
|---|---|---|
|
md5:ad0055009ed45bdca7453f1fe58d953b
|
2.6 GB | Preview Download |
|
md5:d7a7a2247b6750b1909812b8e9e805ba
|
1.9 GB | Preview Download |
|
md5:6a35c3ba269a0b4ec5b1574046f8d528
|
4.3 GB | Download |
|
md5:7f200ab8e08debe632493bad69bcdbd1
|
3.7 GB | Download |
|
md5:1c71ebc048a3da464e27eb509010af99
|
6.0 kB | Preview Download |
Additional details
Dates
- Updated
-
2024-06-06
Software
- Repository URL
- https://github.com/biochunan/AsEP-dataset
- Programming language
- Python
- Development Status
- Active