[1] Z Yuan*, Q Zhou*, L Cai*, et al., Y Chen#, X Zhang# & MQ Zhang#.

SEAM is a spatial single nuclear metabolomics method for dissecting tissue microenvironment.

Nature Methods 18, 1223–1232 (2021).

[2] Z Yuan*#, W Pan*, X Zhao, F Zhao, X Li, Y Zhao, MQ Zhang# & J Yao#.

SODB facilitates comprehensive exploration of spatial omics data.

Nature Methods 20, 387–399 (2023).

[3] Z Yuan*#, F Zhao, S Lin, Y Zhao, J Yao, Y Cui, XY Zhang, Y Zhao#.

Benchmarking spatial clustering methods with spatially resolved transcriptomics data.

Nature Methods (2024).

[4] Z Yuan*#, Y Li*, M Shi, F Yang, J Gao, J Yao# & MQ Zhang#.

SOTIP is a versatile method for microenvironment modeling with spatial omics data.

Nature Communications 13, 7330 (2022).

[5] Z Yuan*#.

MENDER: Fast and scalable tissue structure identification in Spatial Omics Data.

Nature Communications 15, 207 (2024).

[6] S Lin, F Zhao, Z Wu, J Yao, Y Zhao# & Z Yuan#.

Streamlining spatial omics data analysis with Pysodb.

Nature Protocols (2024).

[7] S Lin, Y Cui, F Zhao, et al., BZ Qian, Y Zhao#, Z Yuan#.

Complete spatially resolved gene expression is not necessary for identifying spatial domains.

Cell Genomics (2024).

[8] Z Yuan*# & J Yao#.

Harnessing Computational Spatial Omics to Explore the Spatial Biology Intricacies.

Seminars in Cancer Biology (2023).

[9] T Guo*, Z Yuan*, Y Pan, J Wang, F Chen, MQ Zhang#, X Li#.

SPIRAL: integrating and aligning spatially resolved transcriptomics data across different experiments, conditions, and technologies.

Genome Biology 24, 241 (2023).