E evaluation across diverse biological systems shows that SGFN achieves improved or competitive performance relative to representative baseline methods in reference-based benchmarks, and identifies biologically coherent spatial or functional regions in unlabeled datasets supported by marker-gene, spatial-autocorrelation, cell-type-colocalization, and pathway-enrichment evidence.
A novel Biologically Interpretable multi-modal Graph using Spatial Transcriptomics, called BIGraph-ST, that integrates pathway activity scores and histological image features for robust spatial domain identification and provides biologically interpretable pathway-level representations of domains, which ultimately offer...
Seungeun Lee, Guolon Wang, Kyungtae Kang et al.· bioRxiv· 0 citations
A Spot-Adaptive Structural Rectification method that projects gene expression profiles onto a unit hypersphere to maximize angular distances, effectively separating spots falsely clustered by high total counts and surpasses state-of-the-art methods in spatial clustering.
Huan-Jia Zhao, Shang-Hui Deng, Shunfanyi Li et al.· Proceedings of the Thirty-Fi...· 0 citations
StKAN is introduced, a novel framework integrating Kolmogorov-Arnold Network with variational autoencoder to effectively model spatially resolved gene expression with graph attention network and shows strong potential for downstream analyses, offering deeper insights into disease pathology and tumor invasion.
Jing Lin, Ai-Jing Feng, Yan-Kun Cao et al.· Computational biology and ch...· 0 citations
Spatial transcriptomics (ST) enables the simultaneous measurement of high-throughput gene expression and spatial structural information, offering a powerful means to decipher tissue heterogeneity. However, current spatial domain identification methods struggle to accurately distinguish continuous biological boundaries,...
Jiazhou Chen, Ziru Xiao, Junyu Li et al.· Proceedings of the 32nd ACM...· 0 citations
It is demonstrated that DAHGT-CCI can more accurately reconstruct cell communication networks in complex tissue microenvironments, offering an indispensable computational tool for studying developmental processes, disease mechanisms, and potential therapeutic targets from a spatially resolved perspective.
Wei-Liang Huo, Shuo Yu, Qing-Chen Zhang· Proceedings of the Thirty-Fi...· 0 citations
STORM provides an annotation-free framework for discovering recurrent spatial motifs and identifies a fibroblast barrier architecture whose topological association with immune exclusion is independent of effector abundance, amplified in early-onset disease, and translatable to a deployable pathology-based prognostic bi...
Jia Yao, Yuqiu Yang, Yi Jiang et al.· bioRxiv· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
