Open source code for AlphaFold 2.
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Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
- pytorch
- protein-structure
- alphafold2
An open-source application for biological image analysis
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
A dependency-free cross-platform swiss army knife for PDB files.
- python
- protein
- pdb
- bioinformatics
Schema and generated objects for biolink data model and upper ontology
- biolink
- monarchinitiative
- gene-ontology
- datamodel
Open source tumor evidence matching for sequencing labs and hospitals without molecular tumor boards. Research prototype; oncologist review required.
- bioinformatics
- cancer-research
- computational-biology
- drug-repurposing
Open-source software for exploring and analyzing large, high-dimensional image-derived data.
- cellprofiler-analyst
- cellprofiler
- image-analysis
- machine-learning
OpenBioLink is a resource and evaluation framework for evaluating link prediction models on heterogeneous biomedical graph data.
TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020) https://doi.org/10.1093/bioinformatics/btaa524
- self-attention
- compound-protein-interaction
- transformercpi
- structure-free-virtual-sreening
PyTorch implementation of the MIDAS algorithm for single-cell multimodal data integration (Nature Biotechnology 2024).
- deep-generative-model
- deep-learning
- single-cell-data-integration
- single-cell-multiomics
MCP server for spatial transcriptomics analysis through natural language interfaces.
- bioinformatics
- cell-communication
- deconvolution
- machine-learning
PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"