prtm
deepchem
| prtm | deepchem | |
|---|---|---|
| 1 | 4 | |
| 16 | 5,174 | |
| - | 2.7% | |
| 9.1 | 9.9 | |
| 18 days ago | 2 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
prtm
deepchem
-
Query
You can see a number of splitter implementations from the DeepChem package here. The code is quite elaborate but for your case it may not need to be. Still, if you can use their package for splitting that would be easiest.
- Deepchem – Democratizing Deep-Learning for Drug Discovery
- Deepchem dataset load_tox21()
- How do I transition into bioinformatics from a senior software engineer (14 years of experience)?
What are some alternatives?
chemicalx - A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
torchdrug - A powerful and flexible machine learning platform for drug discovery
Machine-Learning-Guide - Machine learning Guide. Learn all about Machine Learning Tools, Libraries, Frameworks, Large Language Models (LLMs), and Training Models.
deepqmc - Deep learning quantum Monte Carlo for electrons in real space
bidd-molmap - MolMapNet: An Efficient ConvNet with Knowledge-based Molecular Represenations for Molecular Deep Learning
alphafold2 - To eventually become an unofficial Pytorch implementation / replication of Alphafold2, as details of the architecture get released
OpenWorm - Repository for the main Dockerfile with the OpenWorm software stack and project-wide issues
OpenChem - OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
pytorch_tempest - My repo for training neural nets using pytorch-lightning and hydra
caer - High-performance Vision library in Python. Scale your research, not boilerplate.