Author

Yao Li

BGI Group (China)ORCID 0000-0002-5248-3249Unclaimed ORCID profile · follow to get notified of new preprints

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Yao Li4 papers · BGI Research

Biology Disciplines

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Bioinformatics· 2 Developmental Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 3 Assay:spatial transcriptomics· 3 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1 Research Focus:database / resource· 1 Organism:Drosophila· 1

Frequent Co-Authors

Guangyi FaniD· 3 shared Lidong GuoiD· 3 shared Mengyang XuiD· 3 shared Xun XuiD· 3 shared Kai HaniD· 2 shared Shuangsang FangiD· 2 shared An ZengiD· 1 shared Ao CheniD· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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3 shared papersBioinformatics

Guangyi FanORCID

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3 papers

Recent·Most cited

4D Single-Cell Spatial Transcriptomics Reveals Dynamic Morphogenetic Gradients and Regenerative Domains in Planarians

Kai Han, Yuxiaofei Wang, Yao Li, Lidong Guo, Yue Chen, Xiawei Liu, Yaru Lin, Zhi Huang, Qun Liu, Wenjie Guo, Rui Zhang, Wandong Zhao, Langchao Liang, Xiaoyu Wei, Li Zhou, , Mengyang Xu

This study constructs a 4D spatiotemporal transcriptomic map of planarian regeneration using Stereo-seq, identifying dynamic gradients and an injury-induced regenerative zone.

GigaScience · Jan 1, 2026Peer-reviewedDevelopmental Biology

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Shuangsang Fang, Mengyang Xu, Lei Cao, Xiaobin Liu, Marija Bezulj, Liwei Tan, Zhiyuan Yuan, Yao Li, Tianyi Xia, Longyu Guo, Vladimir Kovačević, Junhou Hui, Lidong Guo, Chao Liu, Mengnan Cheng, , Xun Xu

Stereopy provides a framework for analyzing multi-sample spatial transcriptomics data to model comparative and spatiotemporal cellular heterogeneity through three key algorithms.

Nature Communications · Apr 21, 2025Peer-reviewedBioinformatics

SpaGRN: investigating spatially informed regulatory paths for spatially resolved transcriptomics data

Yao Li, Xiaobin Liu, Lidong Guo, Kai Han, Shuangsang Fang, Xinjiang Wan, Dantong Wang, Xun Xu, Ling Jiang, Guangyi Fan, Mengyang Xu

SpaGRN predicts spatially informed gene regulatory networks from spatial transcriptomics data, revealing spatiotemporal regulatory patterns in Drosophila development.

Cell Systems · Apr 1, 2025Peer-reviewedBioinformatics