Open source code for AlphaFold 2.
Repository Index
47,133 repositories indexed
1–24 of 41 · Most stars
AlphaFold 3 inference pipeline.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
- drug-discovery
- quantum-chemistry
- deep-learning
- biology
Official git repository for Biopython (originally converted from CVS)
- python
- bioinformatics
- genomics
- biopython
Official repository for the Boltz biomolecular interaction models
- binding-prediction
- drug-discovery
- protein-structure
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
- pytorch
- protein-structure
- alphafold2
This package contains deep learning models and related scripts for RoseTTAFold
Deep probabilistic analysis of single-cell and spatial omics data
- scrna-seq
- variational-bayes
- variational-autoencoder
- cite-seq
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
- drug-repurposing
- deep-learning
- drug-target-interactions
- toolkit
🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free.
- ai-agents
- bioinformatics
- equity
- genomics
Foundation Models for Genomics & Transcriptomics
Python package for graph neural networks in chemistry and biology
- deep-learning
- graph-neural-networks
- dgl
- cheminformatics
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
- kmer
- dnabert-model
- kmer-format
- gpu
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
- deep-learning
- protein-sequences
- protein-structure
- semi-supervised-learning
Graph-linked unified embedding for single-cell multi-omics data integration
- bioinformatics
- deep-learning
- single-cell
- single-cell-multiomics
Official repository for the ProteinGym benchmarks
- benchmark
- computational-biology
- protein
- protein-design
Sequential regulatory activity predictions with deep convolutional neural networks.
A dependency-free cross-platform swiss army knife for PDB files.
- python
- protein
- pdb
- bioinformatics
GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations
Reference mapping for single-cell genomics
- single-cell
- deep-learning
- rna-seq-analysis
- data-integration
The repository host gives no description.
Native R and Python sample-deletion robustness for omics: candidate certificates, minimum deletion bounds, Bioconductor model refits and donor-level pseudobulk
- bioinformatics
- exact-optimization
- metabolomics
- paired-data
RNA-seq prediction with deep convolutional neural networks.
Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell
- histology
- wsi-images
- pan-cancer-analysis
- genomics