a-r-j/ProteinWorkshop
Benchmarking framework for protein representation learning. Includes a large number of pre-training and downstream task datasets, models and training/task utilities. (ICLR 2024)
This helps computational biologists and drug discovery researchers evaluate and compare different ways to represent protein structures for machine learning. You input various protein datasets and machine learning model configurations, and it provides benchmarks and insights into how well different protein representations perform on tasks like predicting protein function or interactions. The target user is someone working on protein-related machine learning research or applications.
268 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to systematically benchmark different protein structure representation learning models for research or drug discovery applications.
Not ideal if you're looking for a simple, out-of-the-box tool for a single protein analysis task without needing to compare multiple representation learning approaches.
Stars
268
Forks
22
Language
Python
License
MIT
Category
Last pushed
Apr 27, 2025
Commits (30d)
0
Dependencies
32
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