Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
- drug-discovery
- quantum-chemistry
- deep-learning
- biology
Repository Index
47,133 repositories indexed
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Official git repository for Biopython (originally converted from CVS)
- python
- bioinformatics
- genomics
- biopython
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
Biological foundation modeling from molecular to genome scale
🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free.
Cloud-native genomic dataframes and batch computing
- genetics
- vcf
- genomics
- gwas
Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis
Python package for graph neural networks in chemistry and biology
- deep-learning
- graph-neural-networks
- dgl
- cheminformatics
In-memory nucleotide sequence k-mer counting, filtering, graph traversal and more
- dna
- k-mer
- python
- bloom-filter
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
Official release of the ProGen models
- language-model
- protein
- generative-model
Generation of protein sequences and evolutionary alignments via discrete diffusion models
- discrete-diffusion
- generative-model
- multiple-sequence-alignment
- protein-sequences
Spatial Single Cell Analysis in Python
- single-cell-rna-seq
- single-cell-genomics
- spatial-transcriptomics
- spatial-analysis
Generative biopolymer design with rich conditioning.
A tool for semi-automatic cell type classification
- python
- single-cell
- machine-learning
- scrna-seq
Graph-linked unified embedding for single-cell multi-omics data integration
- bioinformatics
- deep-learning
- single-cell
- single-cell-multiomics
Sequential regulatory activity predictions with deep convolutional neural networks.
A dependency-free cross-platform swiss army knife for PDB files.
- python
- protein
- pdb
- bioinformatics
Benchmarking analysis of data integration tools
GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations
UCE is a zero-shot foundation model for single-cell gene expression data