Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
- cell-annotation
- multiplexed-imaging
- mpif
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Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
Adaptive Graph Attention Auto-encoder for Spatial Domain Identification of Spatial Transcriptomics
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Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
MCP server for spatial transcriptomics analysis through natural language interfaces.
Multigrate: multiomic data integration for single-cell genomics
Fast, deterministic cell-type deconvolution for million-bin spatial transcriptomics
Data logistics system enabling real-time pathogen surveillance. Built for the Seattle Flu Study.
Vendor-agnostic, FHIR-Genomics-aligned API contract for cross-vendor NGS interpretation. JSON Schema + TypeScript + Python pydantic.