Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
- pytorch
- protein-structure
- alphafold2
Repository Index
77,852 visible repositories in the index
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Making Protein folding accessible to all!
- bioinformatics
- multiple-sequence-alignment
- protein-structure
- structure-prediction
R toolkit for single cell genomics
- human-cell-atlas
- single-cell-rna-seq
- single-cell-genomics
- cran
MMseqs2: ultra fast and sensitive search and clustering suite
- bioinformatics
- sequence-clustering
- profile-search
- sequence-search
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
The repository host gives no description.
- foundation-model
- gpt
- single-cell
Scientific workflow engine designed for simplicity & scalability. Trivially transition between one off use cases to massive scale production environments
Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis
:christmas_tree:Visualization and annotation of phylogenetic trees
- r
- visualization
- phylogenetic-trees
- annotations
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
[ICLR 2024] DNABERT-2: Efficient Foundation Model and Benchmark for Multi-Species Genome
- dataset
- dna
- dna-processing
- dna-training
A tool for semi-automatic cell type classification
- python
- single-cell
- machine-learning
- scrna-seq
RNA Velocity generalized through dynamical modeling
SCENIC is an R package to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.
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
Benchmarking analysis of data integration tools
Reference mapping for single-cell genomics
- single-cell
- deep-learning
- rna-seq-analysis
- data-integration
Genomic Pretrained Network - GPN, GPN-MSA, PhyloGPN, GPN-Star
- dna
- language-model
- variant-effect-prediction
- genomics
The repository host gives no description.