CMB_2025v15n4

Computational Molecular Biology 2025, Vol.15, No.4, 183-192 http://bioscipublisher.com/index.php/cmb 192 Yang P., Jin K., Yao Y., Jin L., Shao X., Li C., Lu X., and Fan X., 2025, Spatial integration of multi-omics single-cell data with SIMO, Nature Communications, 16(1): 1265. https://doi.org/10.1038/s41467-025-56523-4 Zeira R., Land M., Strzalkowski A., and Raphael B., 2022, Alignment and integration of spatial transcriptomics data, Nature Methods, 19(5): 567-575. https://doi.org/10.1038/s41592-022-01459-6 Zhang W., Huang X., He L., and Zhao X., 2025, Advances in spatial multi-omics technologies, Chinese Science Bulletin, 2024: 1403. https://doi.org/10.1360/TB-2024-1403 Zhang Y., Yu B., Ming W., Zhou X., Wang J., and Chen D., 2024, SpaTopic: a statistical learning framework for exploring tumor spatial architecture from spatially resolved transcriptomic data, Science Advances, 10(39): eadp4942. https://doi.org/10.1126/sciadv.adp4942 Zhao J., Zhang X., Wang G., Lin Y., Liu T., Chang R., and Zhao H., 2024, INSPIRE: interpretable, flexible and spatially-aware integration of multiple spatial transcriptomics datasets from diverse sources, bioRxiv, 23: 6114539. https://doi.org/10.1101/2024.09.23.614539

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