arXiv (All)
open access
GATE-ST: Gene-Aware Text-image Encoder for Spatial Transcriptomics
Spatial transcriptomics enables spatially resolved gene expression analysis from slide-level images while preserving morphological features, providing valuable information for studying disease mechanisms and developing treatments. However, spatial gene expression profiling typically requires expensi
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Reference-informed spatial domain detection using weak supervision for spatial transcriptomics#485207
- A deep learning representation and spatial Bayesian cell-type deconvolution for spatial transcriptomics.#406424
- Data-Adaptive Grassmann Manifold Representations for Spatial Transcriptomics Alignment#1070270
- PaSTel: Anchoring Histology in Spatial Transcriptomics via Multi-Scale Hierarchical Bio-Prior Contrastive Pretraining#609339
- Trainable clustering framework for spatial transcriptomics.#266979
Record · ID 1143291
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive