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#single-cell

CellBRIDGE: Learning Cellular Trajectories via Interaction-Aware Alignment

arXiv cs.LG · 3d ago Cached

CellBRIDGE is a new method that enhances optimal transport for scRNA-seq trajectory inference by incorporating ligand-receptor interaction costs to model cell-cell communication, improving alignment and enabling interpretable in silico perturbations.

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#single-cell

@arcinstitute: PerturbSpace presses a tissue section onto a chip of barcoded microwells. Antibodies in each well tag the cells above w…

X AI KOLs Timeline · 2026-05-26 Cached

PerturbSpace is a spatial transcriptomics method that presses a tissue section onto a chip of barcoded microwells, using antibodies to tag cells with location codes before single-cell sequencing, achieving >90% confident spatial assignment.

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#single-cell

@arcinstitute: Most spatial CRISPR screens require trade-offs in throughput or readout depth. A new preprint from @alexnevue, @Inna_Av…

X AI KOLs Timeline · 2026-05-26 Cached

A new preprint from the Arc Institute introduces PerturbSpace, a method for spatially resolved, multimodal whole-transcriptome CRISPR screens compatible with standard single-cell workflows.

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#single-cell

scShapeBench: Discovering geometry from high dimensional scRNAseq data

arXiv cs.LG · 2026-05-14 Cached

Introduces scShapeBench, a benchmark dataset for shape detection in high-dimensional single-cell data, and scReebTower, a baseline method that uses diffusion geometry and Reeb graphs to classify data shapes into clusters, trajectories, multi-branches, and archetypes.

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#single-cell

GATHER: Convergence-Centric Hyper-Entity Retrieval for Zero-Shot Cell-Type Annotation

arXiv cs.CL · 2026-05-08 Cached

This paper introduces GATHER, a convergence-centric retrieval method for zero-shot cell-type annotation using knowledge graphs, which improves accuracy and reduces LLM costs compared to existing KG-RAG baselines.

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#single-cell

Geometric coherence of single-cell CRISPR perturbations reveals regulatory architecture and predicts cellular stress

Hugging Face Daily Papers · 2026-04-17 Cached

This paper introduces Shesha, a geometric stability metric that quantifies directional coherence of single-cell CRISPR perturbation responses using mean cosine similarity, revealing regulatory architecture and predicting cellular stress across 2,200+ perturbations in five CRISPR datasets.

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