https://github.com/anton-bushuiev/ppiformer-iclr2024-rebuttal
https://github.com/anton-bushuiev/ppiformer-iclr2024-rebuttal
Science Score: 10.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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○DOI references
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✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (5.8%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: anton-bushuiev
- License: mit
- Language: Python
- Default Branch: main
- Size: 279 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
PPIformer demo for ICLR2024 rebuttal
Please note that this code is only intended for the examination by reviewers at ICLR2024. The repository will be siginificantly improved in future.
To install, run the following command from the root of the directory (it assumes having the PPIRef and mutils repositories on the same level with this one).
. scripts/installation/install.sh
You may also want to download the pre-trained models for ddG prediction from zenodo and place them under ./weights/ddg_regression.
Then, to reproduce the test results from the paper, you can run
python scripts/test_ddg_regression.py
The script will make predictions with pre-trained ddG models and calculate the tables reported in our manuscript.
Owner
- Name: Anton Bushuiev
- Login: anton-bushuiev
- Kind: user
- Location: Prague
- Company: Czech Technical University in Prague
- Twitter: AntonBushuiev
- Repositories: 23
- Profile: https://github.com/anton-bushuiev
PhD student. Machine learning / computational biology 🤖🌱