Awesome Ai Bioinformatics
A curated list of awesome AI and Bioinformatics.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Tdc | 889 |  | 4 | 4 months ago | 32 | January 27, 2023 | 34 | mit | Jupyter Notebook | |
| Therapeutics Data Commons: Artificial Intelligence Foundation for Therapeutic Science | ||||||||||
| Lightdock | 234 | 4 months ago | gpl-3.0 | Python | ||||||
| Protein-protein, protein-peptide and protein-DNA docking framework based on the GSO algorithm | ||||||||||
| Dnanalyzer | 122 | 5 months ago | 2 | other | Java | |||||
| Revolutionizing DNA analysis and making it accessible to all through innovative AI-powered analysis and interpretive tools | ||||||||||
| Bio Transformers | 114 | 7 months ago | 8 | apache-2.0 | Python | |||||
| bio-transformers is a wrapper on top of the ESM/Protbert model, trained on millions on proteins and used to predict embeddings. | ||||||||||
| Tutorial | 94 | 4 months ago | Jupyter Notebook | |||||||
| Tutorials on machine learning, artificial intelligence, data science with math explanation and reusable code (in python and R) | ||||||||||
| Graph Network Explainability | 51 | 4 years ago | Jupyter Notebook | |||||||
| Explainability techniques for Graph Networks, applied to a synthetic dataset and an organic chemistry task. Code for the workshop paper "Explainability Techniques for Graph Convolutional Networks" (ICML19) | ||||||||||
| Aiml In Medicine Club | 40 | 3 years ago | 1 | apache-2.0 | ||||||
| Repository for "AI/MD in Medicine" club in clubhouse | ||||||||||
| Synthetic | 37 | a year ago | mit | Python | ||||||
| Symbolic Generators for Complex Networks | ||||||||||
| Nolabs | 30 | 4 months ago | 2 | mit | Python | |||||
| Open source biolab | ||||||||||
| Chromoformer | 24 | 9 months ago | 4 | August 16, 2023 | gpl-3.0 | Python | ||||
| The official code implementation for Chromoformer in PyTorch. (Lee et al., Nature Communications. 2022) | ||||||||||
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