MCP server for spatial transcriptomics analysis through natural language interfaces.
- bioinformatics
- cell-communication
- deconvolution
- machine-learning
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MCP server for spatial transcriptomics analysis through natural language interfaces.
A foundation model-driven whole slide image-scale cell phenotyping method with QuPath integration Resources
Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network
3D shape analysis using deep learning
A versatile single-cell cross-modality translation method via dual-aligned variational autoencoders
Fast, deterministic cell-type deconvolution for million-bin spatial transcriptomics
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UV-first benchmark for protein-ligand docking with reproducible annotation, pocket similarity, and HPC workflows.
A flexible Julia toolkit for high-dimensional cellular profiles
scPair: Boosting single cell multimodal analysis by leveraging single cell atlases and implicit feature selection
Simple webapp for generating small ligand conformers
XitoSBML - the spatial SBML plugin for ImageJ
Accelerated similarity searching of small molecules (bioconductor package)