Published June 20, 2022
| Version 1.2.1
Dataset
Open
Replication Data for: Geometric Transformers for Protein Interface Contact Prediction
Description
This dataset contains replication data for the paper titled "Geometric Transformers for Protein Interface Contact Prediction". The dataset consists of pickled Python dictionaries containing pairs of DGLGraphs that can be used to train and validate protein interface contact prediction models. It also contains our best model checkpoints saved as PyTorch LightningModules. Our GitHub repository, DeepInteract, linked in the "Additional notes" metadata section below provides more details on how we use these files as examples for cross-validation.
Notes
This dataset can be used for training and cross-validation of protein interface contact prediction models via our GitHub repository for DeepInteract (https://github.com/BioinfoMachineLearning/DeepInteract).
Files
Files
(7.0 GB)
| Name | Size | Download all |
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md5:1b3a642ec9f772ab54875d789ee9fefd
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9.6 MB | Download |
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md5:8885b34081e1a8409ee9715c48b54767
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77.2 MB | Download |
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md5:a57152d8580645c788d5fa80b923f6e8
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4.3 GB | Download |
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md5:c59dbab87669fee3f669dc32f00b5d70
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2.4 GB | Download |
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md5:331cf17b557694863a19aa23ba1477a9
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3.0 MB | Download |
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md5:8a1954a0bd01f78e6b57c651e9ed04cb
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40.3 MB | Download |
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md5:1571ef687b62e4c60976f9827700dcb2
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139.8 kB | Download |
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md5:b42dae7e6714066b20df2b3842b5dcfc
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60.5 MB | Download |
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md5:c2c90f736df529eb30f3b5d20b783493
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60.5 MB | Download |
Additional details
Related works
- Cites
- 10.7910/DVN/H93ZKK (DOI)
Funding
- III: Medium: Collaborative Research: Guiding Exploration of Protein Structure Spaces with Deep Learning 1763246
- U.S. National Science Foundation
- ABI Innovation: Deep learning methods for protein bioinformatics 1759934
- U.S. National Science Foundation