A list by @biology · 3 papers · 0 followers
Min Dai, Tivadar Torok, Dawei Sun…·Fei Chen
LARIS identifies cell type-specific and spatially restricted ligand-receptor interactions in spatial transcriptomics data with high accuracy and scalability.
Jialin Liu, Hiroaki Manabe, Weizhou Qian…·Joshua D. Welch
CytoSignal detects and quantifies ligand-receptor signaling interactions at cellular resolution from spatial transcriptomic data, enabling spatial gradient analysis and temporal dynamics prediction.
Lei Shi, Min Dai, Yongbo Zhang…·Xiu‐Jie Wang
CellClick is an interactive platform that improves cell type annotation accuracy in single-cell and spatial omics data through automated and user-guided tools.
Papers closest to the centre of this list, not already in it.
Zhuoxuan LI, Tianjie Wang, Pengtao Liu, Yuanhua Huang
SpatialDM identifies spatially co-expressed ligand-receptor pairs and communication patterns in spatial transcriptomics data with high accuracy and scalability.
Suoqin Jin, Maksim V. Plikus, Qing Hua Nie
The paper introduces CellChat v2, a tool for analyzing cell-cell communication from single-cell and spatial transcriptomics data, including spatial proximity analysis and expanded ligand-receptor databases.
Zixuan Cang, Yanxiang Zhao, Axel A. Almet…·Qing Hua Nie
This paper introduces COMMOT, a method for inferring cell-cell communication in spatial transcriptomics, and demonstrates its effectiveness across multiple datasets and technologies.
Jia Zhao, Xinning Shan, Gefei Wang…·Hongyu Zhao
CONCISE improves spatial ligand-receptor interaction inference by accounting for spatial autocorrelation and measurement errors, reducing false positives and enhancing detection power in spatial transcriptomics data.
Shuai Wang, Jiayin Wang, Jiayi Wang…·Yi Xu
CellSTIC decodes hierarchical cell-cell communication in spatial multi-omics data by integrating multimodal evidence and organizing interactions into a hierarchical semantic representation.
James J. Zhu, Yunguan Wang, Woo Yong Chang…·Tao Wang
The paper introduces a Bayesian framework to map cell-cell interactions from spatial transcriptomics data, revealing new biological insights in cancer and immune responses.
Lucas Dubois, Alexander Petrov, John Jack
This paper introduces a proximity-aware graph attention network to infer cell-cell communication from spatial transcriptomics data, achieving improved performance over existing methods.
Xin Shao, Chengyu Li, Haihong Yang…·Xiaohui Fan
SpaTalk infers cell-cell communication from spatial transcriptomic data using a knowledge graph and graph network, outperforming existing methods on public datasets and revealing insights into tissue communication mechanisms.