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
1–19 of 19 · Most stars
Official repository for the Boltz biomolecular interaction models
- binding-prediction
- drug-discovery
- protein-structure
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
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
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
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
A Python Package for Protein Dynamics Analysis
- python
- protein
- dynamics
A tool for semi-automatic cell type classification
- python
- single-cell
- machine-learning
- scrna-seq
RNA Velocity generalized through dynamical modeling
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
MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in biomedical applications.