arXiv (All)
open access
STRATA: Reinforcement-driven Active Sampling with Tri-paradigm Adaptation for Efficient 3D Spatial Transcriptomics
Spatial transcriptomics (ST) enables joint characterization of tissue morphology and gene expression. However, 3D volumetric ST acquisition remains expensive. AI-driven methods offer a low-cost alternative but remain limited in accuracy, while recent 2D section-wise ST acquisition still rely on dens
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
- 3d-OT: a deep geometry-aware framework for heterogeneous slices alignment of spatial multi-omics.#13580
- MultiPASE: Shape-Aware Comparative 3D Genome Analysis#1386755
- Bridging Biomedical Atlas Ecosystem: Cross-Atlas Alignment And Scalable Tissue Specimen Registration#1006968
- Spectral Graph Features for Reference-free RNA 3D Quality Assessment#172236
- In Vivo Spatial Transcriptomics for Bleeding-free Profiling Human Internal Organs#435636
Record · ID 1490221
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