Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
- drug-discovery
- quantum-chemistry
- deep-learning
- biology
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Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Foundation Models for Genomics & Transcriptomics
Python package for graph neural networks in chemistry and biology
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
A Go package for engineering organisms.
Official repository for the ProteinGym benchmarks
A dependency-free cross-platform swiss army knife for PDB files.
🏃 The go-to single-cell Foundation Model
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
MCP server for spatial transcriptomics analysis through natural language interfaces.
3D shape analysis using deep learning
Fast, deterministic cell-type deconvolution for million-bin spatial transcriptomics
scPair: Boosting single cell multimodal analysis by leveraging single cell atlases and implicit feature selection
XitoSBML - the spatial SBML plugin for ImageJ