Official git repository for Biopython (originally converted from CVS)
- python
- bioinformatics
- genomics
- biopython
Repository Index
47,133 repositories indexed
1–22 of 22 · Most stars
Official repository for the Boltz biomolecular interaction models
- binding-prediction
- drug-discovery
- protein-structure
Code for running RFdiffusion
This package contains deep learning models and related scripts for RoseTTAFold
Chai-1, SOTA model for biomolecular structure prediction
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
OmegaFold Release Code
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
GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations
Open Frontier Biomolecular Intelligence
MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in biomedical applications.