{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T21:44:26Z","timestamp":1791841466805,"version":"4.3.4"},"reference-count":240,"publisher":"Elsevier BV","issue":"4","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T00:00:00Z","timestamp":1769126400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82073145"],"award-info":[{"award-number":["82073145"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["3247040729"],"award-info":[{"award-number":["3247040729"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2024YFC3407700"],"award-info":[{"award-number":["2024YFC3407700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004921","name":"Shanghai Jiao Tong University","doi-asserted-by":"publisher","award":["WH510363003\/018"],"award-info":[{"award-number":["WH510363003\/018"]}],"id":[{"id":"10.13039\/501100004921","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Science Bulletin"],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1016\/j.scib.2026.01.034","type":"journal-article","created":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T02:58:26Z","timestamp":1768964306000},"page":"921-945","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":8,"title":["Mapping biology in space: from spatial transcriptomics platforms to analytical tools and databases"],"prefix":"10.1016","volume":"71","author":[{"given":"Zi-Zhen","family":"Guo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Renyan","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weixiang","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keyu","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuexiang","family":"Ying","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hamid","family":"Alinejad-Rokny","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youqiong","family":"Ye","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.scib.2026.01.034_b0005","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1186\/s13073-022-01075-1","article-title":"An introduction to spatial transcriptomics for biomedical research","volume":"14","author":"Williams","year":"2022","journal-title":"Genome Med"},{"key":"10.1016\/j.scib.2026.01.034_b0010","doi-asserted-by":"crossref","DOI":"10.1126\/science.abq4964","article-title":"The dawn of spatial omics","volume":"381","author":"Bressan","year":"2023","journal-title":"Science"},{"key":"10.1016\/j.scib.2026.01.034_b0015","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1007\/s11427-024-2770-x","article-title":"Advances and applications in single-cell and spatial genomics","volume":"68","author":"Wang","year":"2025","journal-title":"Sci China Life Sci"},{"key":"10.1016\/j.scib.2026.01.034_b0020","doi-asserted-by":"crossref","DOI":"10.1002\/bies.201900221","article-title":"Spatially resolved transcriptomes-next generation tools for tissue exploration","volume":"42","author":"Asp","year":"2020","journal-title":"Bioessays"},{"key":"10.1016\/j.scib.2026.01.034_b0025","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1038\/s41592-022-01409-2","article-title":"Museum of spatial transcriptomics","volume":"19","author":"Moses","year":"2022","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0030","doi-asserted-by":"crossref","first-page":"1743","DOI":"10.1038\/s41592-024-02325-3","article-title":"Systematic comparison of sequencing-based spatial transcriptomic methods","volume":"21","author":"You","year":"2024","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0035","article-title":"Spatial transcriptomics: biotechnologies, computational tools, and neuroscience applications","volume":"9","author":"Wang","year":"2025","journal-title":"Small Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0040","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.gpb.2022.10.001","article-title":"Computational approaches and challenges in spatial transcriptomics","volume":"21","author":"Fang","year":"2023","journal-title":"Genom Proteom Bioinform"},{"key":"10.1016\/j.scib.2026.01.034_b0045","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1186\/s13059-023-03145-y","article-title":"Evaluating spatially variable gene detection methods for spatial transcriptomics data","volume":"25","author":"Chen","year":"2024","journal-title":"Genome Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0050","doi-asserted-by":"crossref","first-page":"1141","DOI":"10.1038\/s41467-025-56080-w","article-title":"Categorization of 34 computational methods to detect spatially variable genes from spatially resolved transcriptomics data","volume":"16","author":"Yan","year":"2025","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0055","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1016\/j.omtn.2021.12.009","article-title":"Computational elucidation of spatial gene expression variation from spatially resolved transcriptomics data","volume":"27","author":"Li","year":"2022","journal-title":"Mol Ther Nucleic Acids"},{"key":"10.1016\/j.scib.2026.01.034_b0060","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btaf131","article-title":"Benchmarking algorithms for spatially variable gene identification in spatial transcriptomics","volume":"41","author":"Chen","year":"2025","journal-title":"Bioinform"},{"key":"10.1016\/j.scib.2026.01.034_b0065","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1186\/s13059-023-03045-1","article-title":"Disparities in spatially variable gene calling highlight the need for benchmarking spatial transcriptomics methods","volume":"24","author":"Charitakis","year":"2023","journal-title":"Genome Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0070","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbac475","article-title":"Benchmarking cell-type clustering methods for spatially resolved transcriptomics data","volume":"24","author":"Cheng","year":"2023","journal-title":"Brief Bioinform"},{"key":"10.1016\/j.scib.2026.01.034_b0075","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1038\/s41592-024-02215-8","article-title":"Benchmarking spatial clustering methods with spatially resolved transcriptomics data","volume":"21","author":"Yuan","year":"2024","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0080","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkaf303","article-title":"Benchmarking computational methods for detecting spatial domains and domain-specific spatially variable genes from spatial transcriptomics data","volume":"53","author":"Kang","year":"2025","journal-title":"Nucleic Acids Res"},{"key":"10.1016\/j.scib.2026.01.034_b0085","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1186\/s13059-024-03361-0","article-title":"Benchmarking clustering, alignment, and integration methods for spatial transcriptomics","volume":"25","author":"Hu","year":"2024","journal-title":"Genome Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0090","doi-asserted-by":"crossref","first-page":"1548","DOI":"10.1038\/s41467-023-37168-7","article-title":"A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics","volume":"14","author":"Li","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0095","doi-asserted-by":"crossref","DOI":"10.1093\/gpbjnl\/qzae057","article-title":"Computational strategies and algorithms for inferring cellular composition of spatial transcriptomics data","volume":"22","author":"Liu","year":"2024","journal-title":"Genom Proteom Bioinform"},{"key":"10.1016\/j.scib.2026.01.034_b0100","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbac245","article-title":"A comprehensive comparison on cell-type composition inference for spatial transcriptomics data","volume":"23","author":"Chen","year":"2022","journal-title":"Brief Bioinform"},{"key":"10.1016\/j.scib.2026.01.034_b0105","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1038\/s41576-021-00370-8","article-title":"Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics","volume":"22","author":"Longo","year":"2021","journal-title":"Nat Rev Genet"},{"key":"10.1016\/j.scib.2026.01.034_b0110","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1038\/s41576-023-00685-8","article-title":"The diversification of methods for studying cell-cell interactions and communication","volume":"25","author":"Armingol","year":"2024","journal-title":"Nat Rev Genet"},{"key":"10.1016\/j.scib.2026.01.034_b0115","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1186\/s12929-022-00879-y","article-title":"Spatial multi-omics analyses of the tumor immune microenvironment","volume":"29","author":"Hsieh","year":"2022","journal-title":"J Biomed Sci"},{"key":"10.1016\/j.scib.2026.01.034_b0120","doi-asserted-by":"crossref","first-page":"6278","DOI":"10.1038\/s41467-021-26614-z","article-title":"Spatially resolved transcriptomics reveals the architecture of the tumor-microenvironment interface","volume":"12","author":"Hunter","year":"2021","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0125","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1126\/science.280.5363.585","article-title":"Visualization of single RNA transcripts in situ","volume":"280","author":"Femino","year":"1998","journal-title":"Science"},{"key":"10.1016\/j.scib.2026.01.034_b0130","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1038\/nmeth.2892","article-title":"Single-cell in situ RNA profiling by sequential hybridization","volume":"11","author":"Lubeck","year":"2014","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0135","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1038\/s41586-019-1049-y","article-title":"Transcriptome-scale super-resolved imaging in tissues by RNA seqfish","volume":"568","author":"Eng","year":"2019","journal-title":"Nature"},{"key":"10.1016\/j.scib.2026.01.034_b0140","doi-asserted-by":"crossref","first-page":"2862","DOI":"10.1242\/dev.138560","article-title":"Single-molecule RNA detection at depth by hybridization chain reaction and tissue hydrogel embedding and clearing","volume":"143","author":"Shah","year":"2016","journal-title":"Development"},{"key":"10.1016\/j.scib.2026.01.034_b0145","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1038\/nmeth.3899","article-title":"Nanoscale imaging of RNA with expansion microscopy","volume":"13","author":"Chen","year":"2016","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0150","doi-asserted-by":"crossref","unstructured":"He S BR., Brown C., Brown E.A., et al. High-plex multiomic analysis in FFPE at subcellular level by spatial molecular imaging. bioRxiv 2021:2021.2011.2003.467020.","DOI":"10.1101\/2021.11.03.467020"},{"key":"10.1016\/j.scib.2026.01.034_b0155","doi-asserted-by":"crossref","DOI":"10.1126\/science.aaa6090","article-title":"RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells","volume":"348","author":"Chen","year":"2015","journal-title":"Science"},{"key":"10.1016\/j.scib.2026.01.034_b0160","doi-asserted-by":"crossref","first-page":"e22","DOI":"10.1093\/nar\/gkx1206","article-title":"Efficient in situ barcode sequencing using padlock probe-based baristaseq","volume":"46","author":"Chen","year":"2018","journal-title":"Nucleic Acids Res"},{"key":"10.1016\/j.scib.2026.01.034_b0165","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1038\/nprot.2014.191","article-title":"Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues","volume":"10","author":"Lee","year":"2015","journal-title":"Nat Protoc"},{"key":"10.1016\/j.scib.2026.01.034_b0170","doi-asserted-by":"crossref","DOI":"10.1126\/science.aax2656","article-title":"Expansion sequencing: spatially precise in situ transcriptomics in intact biological systems","volume":"371","author":"Alon","year":"2021","journal-title":"Science"},{"key":"10.1016\/j.scib.2026.01.034_b0175","doi-asserted-by":"crossref","DOI":"10.1126\/science.aat5691","article-title":"Three-dimensional intact-tissue sequencing of single-cell transcriptional states","volume":"361","author":"Wang","year":"2018","journal-title":"Science"},{"key":"10.1016\/j.scib.2026.01.034_b0180","doi-asserted-by":"crossref","DOI":"10.1126\/science.add3067","article-title":"Spatially resolved single-cell translatomics at molecular resolution","volume":"380","author":"Zeng","year":"2023","journal-title":"Science"},{"key":"10.1016\/j.scib.2026.01.034_b0185","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1126\/science.aaf2403","article-title":"Visualization and analysis of gene expression in tissue sections by spatial transcriptomics","volume":"353","author":"St\u00e5hl","year":"2016","journal-title":"Science"},{"key":"10.1016\/j.scib.2026.01.034_b0190","doi-asserted-by":"crossref","first-page":"1777","DOI":"10.1016\/j.cell.2022.04.003","article-title":"Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays","volume":"185","author":"Chen","year":"2022","journal-title":"Cell"},{"key":"10.1016\/j.scib.2026.01.034_b0195","doi-asserted-by":"crossref","first-page":"1202","DOI":"10.1016\/j.cell.2015.05.002","article-title":"Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets","volume":"161","author":"Macosko","year":"2015","journal-title":"Cell"},{"key":"10.1016\/j.scib.2026.01.034_b0200","doi-asserted-by":"crossref","first-page":"987","DOI":"10.1038\/s41592-019-0548-y","article-title":"High-definition spatial transcriptomics for in situ tissue profiling","volume":"16","author":"Vickovic","year":"2019","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0205","doi-asserted-by":"crossref","unstructured":"Abdulraouf A., Jiang W., Xu Z., et al. Optics-free spatial genomics for mapping mouse brain aging. bioRxiv 2024: 2024.08.06.606712.","DOI":"10.1101\/2024.08.06.606712"},{"key":"10.1016\/j.scib.2026.01.034_b0210","article-title":"Scalable spatial transcriptomics through computational array reconstruction","author":"Hu","year":"2025","journal-title":"Nat Biotechnol"},{"key":"10.1016\/j.scib.2026.01.034_b0215","doi-asserted-by":"crossref","unstructured":"Liao H., Kottapalli S., Huang Y., et al. Optics-free reconstruction of 2D images via DNA barcode proximity graphs. bioRxiv 2024; 2024.08.06.606834.","DOI":"10.1101\/2024.08.06.606834"},{"key":"10.1016\/j.scib.2026.01.034_b0220","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1007\/BF01003828","article-title":"The laser in the Lowry technique for microdissection of freeze-dried tissue slices","volume":"8","author":"Meier-Ruge","year":"1976","journal-title":"Histochem J"},{"key":"10.1016\/j.scib.2026.01.034_b0225","doi-asserted-by":"crossref","first-page":"1622","DOI":"10.1126\/science.aao4277","article-title":"Spatial reconstruction of immune niches by combining photoactivatable reporters and scRNA-seq","volume":"358","author":"Medaglia","year":"2017","journal-title":"Science"},{"key":"10.1016\/j.scib.2026.01.034_b0230","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1038\/nmeth.2804","article-title":"Transcriptome in vivo analysis (TIVA) of spatially defined single cells in live tissue","volume":"11","author":"Lovatt","year":"2014","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0235","doi-asserted-by":"crossref","first-page":"662","DOI":"10.1016\/j.cell.2014.09.038","article-title":"Genome-wide RNA tomography in the zebrafish embryo","volume":"159","author":"Junker","year":"2014","journal-title":"Cell"},{"key":"10.1016\/j.scib.2026.01.034_b0240","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1038\/s41592-018-0009-z","article-title":"Mapping the physical network of cellular interactions","volume":"15","author":"Boisset","year":"2018","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0245","doi-asserted-by":"crossref","first-page":"877","DOI":"10.1038\/nmeth.1253","article-title":"Imaging individual mRNA molecules using multiple singly labeled probes","volume":"5","author":"Raj","year":"2008","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0250","doi-asserted-by":"crossref","first-page":"e151","DOI":"10.1093\/nar\/gkv772","article-title":"Oligonucleotide gap-fill ligation for mutation detection and sequencing in situ","volume":"43","author":"Mignardi","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"10.1016\/j.scib.2026.01.034_b0255","doi-asserted-by":"crossref","first-page":"857","DOI":"10.1038\/nmeth.2563","article-title":"In situ sequencing for RNA analysis in preserved tissue and cells","volume":"10","author":"Ke","year":"2013","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0260","doi-asserted-by":"crossref","first-page":"9232","DOI":"10.1038\/s41467-025-64292-3","article-title":"Systematic benchmarking of high-throughput subcellular spatial transcriptomics platforms across human tumors","volume":"16","author":"Ren","year":"2025","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0265","doi-asserted-by":"crossref","first-page":"8499","DOI":"10.1038\/s41467-025-63414-1","article-title":"Comparison of imaging based single-cell resolution spatial transcriptomics profiling platforms using formalin-fixed paraffin-embedded tumor samples","volume":"16","author":"Ozirmak Lermi","year":"2025","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0270","doi-asserted-by":"crossref","unstructured":"Cook DP, Jensen KB, Wise K, et al. A comparative analysis of imaging-based spatial transcriptomics platforms . bioRxiv 2023: 2023.2012.2013.571385.","DOI":"10.1101\/2023.12.13.571385"},{"key":"10.1016\/j.scib.2026.01.034_b0275","unstructured":"Open source initiative. Licenses & standards. Open source initiative. [cited 2025 april 16]. https:\/\/opensource.org\/licenses. Accessed 16 April 2025."},{"key":"10.1016\/j.scib.2026.01.034_b0280","doi-asserted-by":"crossref","first-page":"940","DOI":"10.1016\/j.csbj.2023.01.016","article-title":"A guidebook of spatial transcriptomic technologies, data resources and analysis approaches","volume":"21","author":"Yue","year":"2023","journal-title":"Comput Struct Biotechnol J"},{"key":"10.1016\/j.scib.2026.01.034_b0285","doi-asserted-by":"crossref","first-page":"4613","DOI":"10.1093\/bioinformatics\/btac544","article-title":"Stitching and registering highly multiplexed whole-slide images of tissues and tumors using Ashlar","volume":"38","author":"Muhlich","year":"2022","journal-title":"Bioinformatics"},{"key":"10.1016\/j.scib.2026.01.034_b0290","doi-asserted-by":"crossref","first-page":"4988","DOI":"10.1038\/s41598-017-04567-y","article-title":"Mist: accurate and scalable microscopy image stitching tool with stage modeling and error minimization","volume":"7","author":"Chalfoun","year":"2017","journal-title":"Sci Rep"},{"key":"10.1016\/j.scib.2026.01.034_b0295","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1186\/1471-2105-13-316","article-title":"Terastitcher\u2014a tool for fast automatic 3D-stitching of teravoxel-sized microscopy images","volume":"13","author":"Bria","year":"2012","journal-title":"BMC Bioinform"},{"key":"10.1016\/j.scib.2026.01.034_b0300","doi-asserted-by":"crossref","first-page":"1463","DOI":"10.1093\/bioinformatics\/btp184","article-title":"Globally optimal stitching of tiled 3D microscopic image acquisitions","volume":"25","author":"Preibisch","year":"2009","journal-title":"Bioinformatics"},{"key":"10.1016\/j.scib.2026.01.034_b0305","doi-asserted-by":"crossref","first-page":"6517","DOI":"10.1021\/acs.analchem.3c05686","article-title":"Spot-based global registration for subpixel stitching of single-molecule resolution images for tissue-scale spatial transcriptomics","volume":"96","author":"Yeo","year":"2024","journal-title":"Anal Chem"},{"key":"10.1016\/j.scib.2026.01.034_b0310","doi-asserted-by":"crossref","first-page":"870","DOI":"10.1038\/s41592-019-0501-0","article-title":"Bigstitcher: reconstructing high-resolution image datasets of cleared and expanded samples","volume":"16","author":"H\u00f6rl","year":"2019","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0315","series-title":"In: Proceedings of the 2016 IEEE 13th international symposium on biomedical imaging (ISBI)","article-title":"Robust registration of calcium images by learned contrast synthesis","author":"Bogovic","year":"2016"},{"key":"10.1016\/j.scib.2026.01.034_b0320","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1038\/s41592-024-02199-5","article-title":"Spatial landmark detection and tissue registration with deep learning","volume":"21","author":"Ekvall","year":"2024","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0325","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1038\/d41586-019-02477-9","article-title":"Starfish enterprise: finding RNA patterns in single cells","volume":"572","author":"Perkel","year":"2019","journal-title":"Nature"},{"key":"10.1016\/j.scib.2026.01.034_b0330","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1038\/s41587-021-01044-w","article-title":"Cell segmentation in imaging-based spatial transcriptomics","volume":"40","author":"Petukhov","year":"2022","journal-title":"Nat Biotechnol"},{"key":"10.1016\/j.scib.2026.01.034_b0335","unstructured":"Canete NNA, Patrick E. simpleSeg: a package to perform simple cell segmentation; 2023."},{"key":"10.1016\/j.scib.2026.01.034_b0340","series-title":"In: Medical Image Computing and Computer Assisted Intervention (MICCAI)","article-title":"Cell detection with star-convex polygons","author":"Schmidt","year":"2018"},{"key":"10.1016\/j.scib.2026.01.034_b0345","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1038\/s41592-020-01018-x","article-title":"Cellpose: a generalist algorithm for cellular segmentation","volume":"18","author":"Stringer","year":"2021","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0350","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btad362","article-title":"Optimization-based decoding of imaging spatial transcriptomics data","volume":"39","author":"Bryan","year":"2023","journal-title":"Bioinformatics"},{"key":"10.1016\/j.scib.2026.01.034_b0355","unstructured":"Genomics x. Xenium ranger vVersion 3.0. 10\u00d7 genomics. https:\/\/www.10xgenomics.com\/support\/software\/xenium-ranger\/latest. 2024"},{"key":"10.1016\/j.scib.2026.01.034_b0360","unstructured":"Easi-fish nextflow pipeline. https:\/\/janeliascicomp.github.io\/multifish\/."},{"key":"10.1016\/j.scib.2026.01.034_b0365","unstructured":"Space ranger and loupe browser. https:\/\/www.10xgenomics.com\/support\/software\/space-ranger\/latest. 2020."},{"key":"10.1016\/j.scib.2026.01.034_b0370","unstructured":"Li M, Liu H, Li M, et al. StereoCell enables high accuracy single cell segmentation for spatial transcriptomic dataset. bioRxiv 2023: 2023.2002.2028.530414."},{"key":"10.1016\/j.scib.2026.01.034_b0375","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1038\/s41592-021-01358-2","article-title":"Squidpy: a scalable framework for spatial omics analysis","volume":"19","author":"Palla","year":"2022","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0380","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btae458","article-title":"SpatialQC: automated quality control for spatial transcriptome data","volume":"40","author":"Mao","year":"2024","journal-title":"Bioinformatics"},{"key":"10.1016\/j.scib.2026.01.034_b0385","doi-asserted-by":"crossref","unstructured":"Totty M, Hicks SC, Guo B Spotsweeper: spatially-aware quality control for spatial transcriptomics. bioRxiv 2024; 2024.2006.2006.597765.","DOI":"10.1101\/2024.06.06.597765"},{"key":"10.1016\/j.scib.2026.01.034_b0390","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1038\/s41592-022-01560-w","article-title":"Sprod for de-noising spatially resolved transcriptomics data based on position and image information","volume":"19","author":"Wang","year":"2022","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0395","doi-asserted-by":"crossref","unstructured":"Cui Y, Wang R, Zeng X, et al. DenoiseST: a dual-channel unsupervised deep learning-based denoising method to identify spatial domains and functionally variable genes in spatial transcriptomics. bioRxiv 2024; 2024.2003.2004.583438.","DOI":"10.1101\/2024.03.04.583438"},{"key":"10.1016\/j.scib.2026.01.034_b0400","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1038\/s41587-020-0739-1","article-title":"Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2","volume":"39","author":"Stickels","year":"2021","journal-title":"Nat Biotechnol"},{"key":"10.1016\/j.scib.2026.01.034_b0405","doi-asserted-by":"crossref","first-page":"2971","DOI":"10.1038\/s41467-022-30587-y","article-title":"SpotClean adjusts for spot swapping in spatial transcriptomics data","volume":"13","author":"Ni","year":"2022","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0410","doi-asserted-by":"crossref","first-page":"1028","DOI":"10.1038\/s41467-023-36707-6","article-title":"Spatial transcriptomics reveals niche-specific enrichment and vulnerabilities of radial glial stem-like cells in malignant gliomas","volume":"14","author":"Ren","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0415","unstructured":"Lopez R, Nazaret A, Langevin M, et al. A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements. arXiv:1905.02269; 2019."},{"key":"10.1016\/j.scib.2026.01.034_b0420","doi-asserted-by":"crossref","first-page":"1352","DOI":"10.1038\/s41592-021-01264-7","article-title":"Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram","volume":"18","author":"Biancalani","year":"2021","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0425","doi-asserted-by":"crossref","first-page":"e107","DOI":"10.1093\/nar\/gkaa740","article-title":"SpaGE: spatial gene enhancement using scRNA-seq","volume":"48","author":"Abdelaal","year":"2020","journal-title":"Nucleic Acids Res"},{"key":"10.1016\/j.scib.2026.01.034_b0430","doi-asserted-by":"crossref","first-page":"1271","DOI":"10.1038\/s42003-024-06964-2","article-title":"Imputing spatial transcriptomics through gene network constructed from protein language model","volume":"7","author":"Zeng","year":"2024","journal-title":"Commun Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0435","doi-asserted-by":"crossref","first-page":"i299","DOI":"10.1093\/bioinformatics\/btab298","article-title":"stPlus: a reference-based method for the accurate enhancement of spatial transcriptomics","volume":"37","author":"Shengquan","year":"2021","journal-title":"Bioinformatics"},{"key":"10.1016\/j.scib.2026.01.034_b0440","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1038\/s41592-018-0229-2","article-title":"Deep generative modeling for single-cell transcriptomics","volume":"15","author":"Lopez","year":"2018","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0445","doi-asserted-by":"crossref","DOI":"10.1093\/gigascience\/giad097","article-title":"EAGS: efficient and adaptive Gaussian smoothing applied to high-resolved spatial transcriptomics","volume":"13","author":"Lv","year":"2024","journal-title":"GigaScience"},{"key":"10.1016\/j.scib.2026.01.034_b0450","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbac116","article-title":"SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression","volume":"23","author":"Liu","year":"2022","journal-title":"Brief Bioinform"},{"key":"10.1016\/j.scib.2026.01.034_b0455","doi-asserted-by":"crossref","unstructured":"Maher K, Wu M, Zhou Y, et al. Mitigating autocorrelation during spatially resolved transcriptomics data analysis. bioRxiv 2023;2023.2006.2030.547258.","DOI":"10.1101\/2023.06.30.547258"},{"key":"10.1016\/j.scib.2026.01.034_b0460","doi-asserted-by":"crossref","first-page":"i521","DOI":"10.1093\/bioinformatics\/btae253","article-title":"Sprite: improving spatial gene expression imputation with gene and cell networks","volume":"40","author":"Sun","year":"2024","journal-title":"Bioinformatics"},{"key":"10.1016\/j.scib.2026.01.034_b0465","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbad013","article-title":"DIST: spatial transcriptomics enhancement using deep learning","volume":"24","author":"Zhao","year":"2023","journal-title":"Brief Bioinform"},{"key":"10.1016\/j.scib.2026.01.034_b0470","doi-asserted-by":"crossref","first-page":"1375","DOI":"10.1038\/s41587-021-00935-2","article-title":"Spatial transcriptomics at subspot resolution with bayesspace","volume":"39","author":"Zhao","year":"2021","journal-title":"Nat Biotechnol"},{"key":"10.1016\/j.scib.2026.01.034_b0475","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1016\/j.cels.2023.03.008","article-title":"Deciphering tumor ecosystems at super resolution from spatial transcriptomics with TESLA","volume":"14","author":"Hu","year":"2023","journal-title":"Cell Syst"},{"key":"10.1016\/j.scib.2026.01.034_b0480","doi-asserted-by":"crossref","first-page":"1372","DOI":"10.1038\/s41587-023-02019-9","article-title":"Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology","volume":"42","author":"Zhang","year":"2024","journal-title":"Nat Biotechnol"},{"key":"10.1016\/j.scib.2026.01.034_b0485","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1038\/s41587-021-01075-3","article-title":"Super-resolved spatial transcriptomics by deep data fusion","volume":"40","author":"Bergenstr\u00e5hle","year":"2022","journal-title":"Nat Biotechnol"},{"key":"10.1016\/j.scib.2026.01.034_b0490","doi-asserted-by":"crossref","unstructured":"Hua Y, Zhang Y, Guo Z, et al. ImSpiRE: image feature-aided spatial resolution enhancement method. bioRxiv 2023;2023.2005.2004.539342.","DOI":"10.1101\/2023.05.04.539342"},{"key":"10.1016\/j.scib.2026.01.034_b0495","doi-asserted-by":"crossref","first-page":"656","DOI":"10.1038\/s41586-024-07113-9","article-title":"An atlas of epithelial cell states and plasticity in lung adenocarcinoma","volume":"627","author":"Han","year":"2024","journal-title":"Nature"},{"key":"10.1016\/j.scib.2026.01.034_b0500","doi-asserted-by":"crossref","first-page":"1550","DOI":"10.1038\/s41591-023-02371-y","article-title":"Pan-cancer T cell atlas links a cellular stress response state to immunotherapy resistance","volume":"29","author":"Chu","year":"2023","journal-title":"Nat Med"},{"key":"10.1016\/j.scib.2026.01.034_b0505","doi-asserted-by":"crossref","first-page":"2626","DOI":"10.1158\/2159-8290.CD-21-1658","article-title":"The single-cell immunogenomic landscape of B and plasma cells in early-stage lung adenocarcinoma","volume":"12","author":"Hao","year":"2022","journal-title":"Cancer Discov"},{"key":"10.1016\/j.scib.2026.01.034_b0510","doi-asserted-by":"crossref","first-page":"6541","DOI":"10.1038\/s41467-024-50837-5","article-title":"Tissue characterization at an enhanced resolution across spatial omics platforms with deep generative model","volume":"15","author":"Li","year":"2024","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0515","doi-asserted-by":"crossref","first-page":"e8746","DOI":"10.15252\/msb.20188746","article-title":"Current best practices in single-cell RNA-seq analysis: a tutorial","volume":"15","author":"Luecken","year":"2019","journal-title":"Mol Syst Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0520","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1186\/s13059-024-03183-0","article-title":"A comparison of marker gene selection methods for single-cell RNA sequencing data","volume":"25","author":"Pullin","year":"2024","journal-title":"Genome Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0525","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1093\/bioinformatics\/btp616","article-title":"edgeR: a bioconductor package for differential expression analysis of digital gene expression data","volume":"26","author":"Robinson","year":"2010","journal-title":"Bioinformatics"},{"key":"10.1016\/j.scib.2026.01.034_b0530","doi-asserted-by":"crossref","first-page":"550","DOI":"10.1186\/s13059-014-0550-8","article-title":"Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2","volume":"15","author":"Love","year":"2014","journal-title":"Genome Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0535","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1186\/s13059-024-03303-w","article-title":"Gene count normalization in single-cell imaging-based spatially resolved transcriptomics","volume":"25","author":"Atta","year":"2024","journal-title":"Genome Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0540","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1186\/s13059-025-03565-y","article-title":"Spanorm: spatially-aware normalization for spatial transcriptomics data","volume":"26","author":"Salim","year":"2025","journal-title":"Genome Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0545","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1093\/jmcb\/mjaa028","article-title":"Transcriptional output, cell-type densities, and normalization in spatial transcriptomics","volume":"12","author":"Saiselet","year":"2020","journal-title":"J Mol Cell Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0550","article-title":"Spatial transcriptomics: technical aspects of recent developments and their applications in neuroscience and cancer research","volume":"10","author":"Park","year":"2023","journal-title":"Adv Sci (Weinh)"},{"key":"10.1016\/j.scib.2026.01.034_b0555","article-title":"Accurate inference of genome-wide spatial expression with iSpatial","volume":"8","author":"Zhang","year":"2022","journal-title":"Sci Adv"},{"key":"10.1016\/j.scib.2026.01.034_b0560","doi-asserted-by":"crossref","unstructured":"Li Z, Patel ZM, Song D, et al. Benchmarking computational methods to identify spatially variable genes and peaks. bioRxiv 2023: 2023.2012.2002.569717.","DOI":"10.1101\/2023.12.02.569717"},{"key":"10.1016\/j.scib.2026.01.034_b0565","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1038\/nmeth.4636","article-title":"SpatialDE: identification of spatially variable genes","volume":"15","author":"Svensson","year":"2018","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0570","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1038\/nmeth.4634","article-title":"Identification of spatial expression trends in single-cell gene expression data","volume":"15","author":"Edsg\u00e4rd","year":"2018","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0575","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1038\/s41592-019-0701-7","article-title":"Statistical analysis of spatial expression patterns for spatially resolved transcriptomic studies","volume":"17","author":"Sun","year":"2020","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0580","doi-asserted-by":"crossref","first-page":"1342","DOI":"10.1038\/s41592-021-01255-8","article-title":"SpaGCN: integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network","volume":"18","author":"Hu","year":"2021","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0585","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btae027","article-title":"DESpace: spatially variable gene detection via differential expression testing of spatial clusters","volume":"40","author":"Cai","year":"2024","journal-title":"Bioinformatics"},{"key":"10.1016\/j.scib.2026.01.034_b0590","doi-asserted-by":"crossref","first-page":"4135","DOI":"10.1093\/bioinformatics\/btac457","article-title":"Identification of cell-type-specific spatially variable genes accounting for excess zeros","volume":"38","author":"Yu","year":"2022","journal-title":"Bioinformatics"},{"key":"10.1016\/j.scib.2026.01.034_b0595","doi-asserted-by":"crossref","first-page":"1076","DOI":"10.1038\/s41592-022-01575-3","article-title":"Cell type-specific inference of differential expression in spatial transcriptomics","volume":"19","author":"Cable","year":"2022","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0600","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1186\/s13059-024-03245-3","article-title":"spVC for the detection and interpretation of spatial gene expression variation","volume":"25","author":"Yu","year":"2024","journal-title":"Genome Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0605","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btad431","article-title":"Unravelling spatial gene associations with SEAGAL: a python package for spatial transcriptomics data analysis and visualization","volume":"39","author":"Wang","year":"2023","journal-title":"Bioinformatics"},{"key":"10.1016\/j.scib.2026.01.034_b0610","doi-asserted-by":"crossref","first-page":"5057","DOI":"10.1038\/s41467-024-49171-7","article-title":"Dissecting tumor microenvironment from spatially resolved transcriptomics data by heterogeneous graph learning","volume":"15","author":"Zuo","year":"2024","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0615","doi-asserted-by":"crossref","first-page":"1843","DOI":"10.1038\/s41592-024-02415-2","article-title":"Ficture: scalable segmentation-free analysis of submicron-resolution spatial transcriptomics","volume":"21","author":"Si","year":"2024","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0620","doi-asserted-by":"crossref","first-page":"1470","DOI":"10.1038\/s41592-024-02201-0","article-title":"scGPT: toward building a foundation model for single-cell multi-omics using generative AI","volume":"21","author":"Cui","year":"2024","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0625","doi-asserted-by":"crossref","first-page":"616","DOI":"10.1038\/s41586-023-06139-9","article-title":"Transfer learning enables predictions in network biology","volume":"618","author":"Theodoris","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.scib.2026.01.034_b0630","doi-asserted-by":"crossref","unstructured":"Wang Q, Zhu H, Hu Y, et al. Hierarchical interpretation of out-of-distribution cells using bottlenecked transformer. bioRxiv 2024;2024.2012.2017.628533.","DOI":"10.1101\/2024.12.17.628533"},{"key":"10.1016\/j.scib.2026.01.034_b0635","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btaf094","article-title":"ENACT: end-to-end analysis of visium high definition (HD) data","volume":"41","author":"Kamel","year":"2025","journal-title":"Bioinformatics"},{"key":"10.1016\/j.scib.2026.01.034_b0640","doi-asserted-by":"crossref","first-page":"2848","DOI":"10.1038\/s41467-024-47152-4","article-title":"Pianno: a probabilistic framework automating semantic annotation for spatial transcriptomics","volume":"15","author":"Zhou","year":"2024","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0645","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbad533","article-title":"Spann: annotating single-cell resolution spatial transcriptome data with scRNA-seq data","volume":"25","author":"Yuan","year":"2024","journal-title":"Brief Bioinform"},{"key":"10.1016\/j.scib.2026.01.034_b0650","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1038\/s41587-021-01139-4","article-title":"Cell2location maps fine-grained cell types in spatial transcriptomics","volume":"40","author":"Kleshchevnikov","year":"2022","journal-title":"Nat Biotechnol"},{"key":"10.1016\/j.scib.2026.01.034_b0655","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1038\/s41587-021-00830-w","article-title":"Robust decomposition of cell type mixtures in spatial transcriptomics","volume":"40","author":"Cable","year":"2022","journal-title":"Nat Biotechnol"},{"key":"10.1016\/j.scib.2026.01.034_b0660","doi-asserted-by":"crossref","first-page":"2339","DOI":"10.1038\/s41467-022-30033-z","article-title":"Reference-free cell type deconvolution of multi-cellular pixel-resolution spatially resolved transcriptomics data","volume":"13","author":"Miller","year":"2022","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0665","doi-asserted-by":"crossref","unstructured":"Singh R, He X, Park AK, et al. RETROFIT: reference-free deconvolution of cell-type mixtures in spatial transcriptomics. bioRxiv 2023; 2023.2006.2007.544126.","DOI":"10.1101\/2023.06.07.544126"},{"key":"10.1016\/j.scib.2026.01.034_b0670","doi-asserted-by":"crossref","first-page":"7848","DOI":"10.1038\/s41467-023-43629-w","article-title":"Integrating spatial and single-cell transcriptomics data using deep generative models with spatialscope","volume":"14","author":"Wan","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0675","doi-asserted-by":"crossref","first-page":"662","DOI":"10.1038\/s41592-022-01480-9","article-title":"Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution prediction and cell type deconvolution","volume":"19","author":"Li","year":"2022","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0685","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btac805","article-title":"Benchmarking and integration of methods for deconvoluting spatial transcriptomic data","volume":"39","author":"Yan","year":"2023","journal-title":"Bioinformatics"},{"key":"10.1016\/j.scib.2026.01.034_b0690","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1038\/s41392-024-01947-5","article-title":"Tertiary lymphoid structures in diseases: immune mechanisms and therapeutic advances","volume":"9","author":"Zhao","year":"2024","journal-title":"Signal Transduct Target Ther"},{"key":"10.1016\/j.scib.2026.01.034_b0695","doi-asserted-by":"crossref","first-page":"5233","DOI":"10.1038\/s41598-019-41695-z","article-title":"From Louvain to Leiden: guaranteeing well-connected communities","volume":"9","author":"Traag","year":"2019","journal-title":"Sci Rep"},{"key":"10.1016\/j.scib.2026.01.034_b0700","doi-asserted-by":"crossref","first-page":"5029","DOI":"10.1038\/s41467-023-40271-4","article-title":"Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response","volume":"14","author":"Arora","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0705","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1038\/s42003-021-01959-9","article-title":"Genomic profiling reveals heterogeneous populations of ductal carcinoma in situ of the breast","volume":"4","author":"Nagasawa","year":"2021","journal-title":"Commun Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0710","doi-asserted-by":"crossref","first-page":"289","DOI":"10.32614\/RJ-2016-021","article-title":"Mclust 5: clustering, classification and density estimation using gaussian finite mixture models","volume":"8","author":"Scrucca","year":"2016","journal-title":"R J"},{"key":"10.1016\/j.scib.2026.01.034_b0715","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1038\/s42003-024-06349-5","article-title":"SpatialPrompt: spatially aware scalable and accurate tool for spot deconvolution and domain identification in spatial transcriptomics","volume":"7","author":"Swain","year":"2024","journal-title":"Commun Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0720","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1038\/s41588-024-01664-3","article-title":"Banksy unifies cell typing and tissue domain segmentation for scalable spatial omics data analysis","volume":"56","author":"Singhal","year":"2024","journal-title":"Nat Genet"},{"key":"10.1016\/j.scib.2026.01.034_b0725","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1186\/s13059-021-02286-2","article-title":"Giotto: a toolbox for integrative analysis and visualization of spatial expression data","volume":"22","author":"Dries","year":"2021","journal-title":"Genome Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0730","doi-asserted-by":"crossref","first-page":"1739","DOI":"10.1038\/s41467-022-29439-6","article-title":"Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder","volume":"13","author":"Dong","year":"2022","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0735","doi-asserted-by":"crossref","first-page":"1155","DOI":"10.1038\/s41467-023-36796-3","article-title":"Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with graphst","volume":"14","author":"Long","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0740","doi-asserted-by":"crossref","first-page":"e131","DOI":"10.1093\/nar\/gkac901","article-title":"DeepST: identifying spatial domains in spatial transcriptomics by deep learning","volume":"50","author":"Xu","year":"2022","journal-title":"Nucleic Acids Res"},{"key":"10.1016\/j.scib.2026.01.034_b0745","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1038\/s41588-025-02120-6","article-title":"Quantitative characterization of cell niches in spatially resolved omics data","volume":"57","author":"Birk","year":"2025","journal-title":"Nat Genet"},{"key":"10.1016\/j.scib.2026.01.034_b0750","doi-asserted-by":"crossref","unstructured":"Bernstein MN, Scott D, Hession CC, et al. Monkeybread: a python toolkit for the analysis of cellular niches in single-cell resolution spatial transcriptomics data. bioRxiv 2023;2023.2009.2014.557736.","DOI":"10.1101\/2023.09.14.557736"},{"key":"10.1016\/j.scib.2026.01.034_b0755","article-title":"The spatial multi-omics revolution in cancer therapy: precision redefined","volume":"5","author":"Du","year":"2024","journal-title":"Cell Rep Med"},{"key":"10.1016\/j.scib.2026.01.034_b0760","doi-asserted-by":"crossref","first-page":"1546","DOI":"10.1126\/science.1235122","article-title":"Cancer genome landscapes","volume":"339","author":"Vogelstein","year":"2013","journal-title":"Science"},{"key":"10.1016\/j.scib.2026.01.034_b0765","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1038\/s41586-022-05023-2","article-title":"Spatially resolved clonal copy number alterations in benign and malignant tissue","volume":"608","author":"Erickson","year":"2022","journal-title":"Nature"},{"key":"10.1016\/j.scib.2026.01.034_b0770","doi-asserted-by":"crossref","DOI":"10.1088\/1478-3975\/abbe99","article-title":"STARCH: copy number and clone inference from spatial transcriptomics data","volume":"18","author":"Elyanow","year":"2021","journal-title":"Phys Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0775","doi-asserted-by":"crossref","first-page":"933","DOI":"10.1038\/s41467-023-36560-7","article-title":"Reconstruction of the tumor spatial microenvironment along the malignant-boundary-nonmalignant axis","volume":"14","author":"Xun","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0780","doi-asserted-by":"crossref","first-page":"8223","DOI":"10.1038\/s41467-024-52445-9","article-title":"Detecting anomalous anatomic regions in spatial transcriptomics with stands","volume":"15","author":"Xu","year":"2024","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0785","doi-asserted-by":"crossref","unstructured":"Jensen A, Crowell HL, Reguant AP, et al. In situ inference of copy number variations in image-based spatial transcriptomics. bioRxiv 2025; 2025.2007.2002.662761.","DOI":"10.1101\/2025.07.02.662761"},{"key":"10.1016\/j.scib.2026.01.034_b0790","doi-asserted-by":"crossref","first-page":"e1594","DOI":"10.1002\/ctm2.1594","article-title":"Spatial transcriptomics reveals prognosis-associated cellular heterogeneity in the papillary thyroid carcinoma microenvironment","volume":"14","author":"Yan","year":"2024","journal-title":"Clin Transl Med"},{"key":"10.1016\/j.scib.2026.01.034_b0795","doi-asserted-by":"crossref","first-page":"2060","DOI":"10.1038\/s12276-022-00896-9","article-title":"Delineating the dynamic evolution from preneoplasia to invasive lung adenocarcinoma by integrating single-cell RNA sequencing and spatial transcriptomics","volume":"54","author":"Zhu","year":"2022","journal-title":"Exp Mol Med"},{"key":"10.1016\/j.scib.2026.01.034_b0800","doi-asserted-by":"crossref","first-page":"4388","DOI":"10.1038\/s41467-024-48700-8","article-title":"Single-cell and spatial transcriptomics analysis of non-small cell lung cancer","volume":"15","author":"De Zuani","year":"2024","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0805","doi-asserted-by":"crossref","first-page":"7739","DOI":"10.1038\/s41467-023-43120-6","article-title":"Robust mapping of spatiotemporal trajectories and cell-cell interactions in healthy and diseased tissues","volume":"14","author":"Pham","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0810","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1038\/s41592-024-02266-x","article-title":"Spatial transition tensor of single cells","volume":"21","author":"Zhou","year":"2024","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0815","article-title":"SIRV: spatial inference of RNA velocity at the single-cell resolution","volume":"6","author":"Abdelaal","year":"2024","journal-title":"NAR Genom Bioinform"},{"key":"10.1016\/j.scib.2026.01.034_b0820","article-title":"Inferring cell trajectories of spatial transcriptomics via optimal transport analysis","volume":"16","author":"Shen","year":"2025","journal-title":"Cell Syst"},{"key":"10.1016\/j.scib.2026.01.034_b0825","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1038\/s41587-019-0071-9","article-title":"A comparison of single-cell trajectory inference methods","volume":"37","author":"Saelens","year":"2019","journal-title":"Nat Biotechnol"},{"key":"10.1016\/j.scib.2026.01.034_b0830","article-title":"Recent advances in trajectory inference from single-cell omics data","volume":"27","author":"Deconinck","year":"2021","journal-title":"Curr Opin Syst Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0835","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.1038\/s41467-020-14766-3","article-title":"Trajectory-based differential expression analysis for single-cell sequencing data","volume":"11","author":"Van den Berge","year":"2020","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0840","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1038\/s41392-024-01888-z","article-title":"Cell-cell communication: new insights and clinical implications","volume":"9","author":"Su","year":"2024","journal-title":"Signal Transduct Target Ther"},{"key":"10.1016\/j.scib.2026.01.034_b0845","doi-asserted-by":"crossref","DOI":"10.3390\/cells12151970","article-title":"A review of single-cell RNA-seq annotation, integration, and cell-cell communication","volume":"12","author":"Cheng","year":"2023","journal-title":"Cells"},{"key":"10.1016\/j.scib.2026.01.034_b0850","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.semcancer.2023.07.001","article-title":"The promising application of cell-cell interaction analysis in cancer from single-cell and spatial transcriptomics","volume":"95","author":"Wang","year":"2023","journal-title":"Semin Cancer Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0855","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1038\/s41589-021-00790-x","article-title":"Strategies for monitoring cell-cell interactions","volume":"17","author":"Bechtel","year":"2021","journal-title":"Nat Chem Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0860","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1186\/s13059-022-02692-0","article-title":"De novo reconstruction of cell interaction landscapes from single-cell spatial transcriptome data with DeepLinc","volume":"23","author":"Li","year":"2022","journal-title":"Genome Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0865","doi-asserted-by":"crossref","first-page":"2084","DOI":"10.1038\/s41467-020-15968-5","article-title":"Inferring spatial and signaling relationships between cells from single cell transcriptomic data","volume":"11","author":"Cang","year":"2020","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0870","doi-asserted-by":"crossref","first-page":"10628","DOI":"10.1038\/s41467-024-54973-w","article-title":"NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis","volume":"15","author":"Agrawal","year":"2024","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0875","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1186\/s13059-022-02663-5","article-title":"Explainable multiview framework for dissecting spatial relationships from highly multiplexed data","volume":"23","author":"Tanevski","year":"2022","journal-title":"Genome Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0880","doi-asserted-by":"crossref","DOI":"10.1093\/gigascience\/giae078","article-title":"StereoSiTE: a framework to spatially and quantitatively profile the cellular neighborhood organized iTME","volume":"13","author":"Liu","year":"2024","journal-title":"Gigascience"},{"key":"10.1016\/j.scib.2026.01.034_b0885","doi-asserted-by":"crossref","first-page":"7101","DOI":"10.1038\/s41467-024-51329-2","article-title":"Deciphering cell-cell communication at single-cell resolution for spatial transcriptomics with subgraph-based graph attention network","volume":"15","author":"Yang","year":"2024","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0890","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1016\/j.cels.2024.05.001","article-title":"Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding","volume":"15","author":"Li","year":"2024","journal-title":"Cell Syst"},{"key":"10.1016\/j.scib.2026.01.034_b0895","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1681\/ASN.2021081150","article-title":"Spatially resolved transcriptomic analysis of acute kidney injury in a female murine model","volume":"33","author":"Dixon","year":"2022","journal-title":"J Am Soc Nephrol"},{"key":"10.1016\/j.scib.2026.01.034_b0900","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbaa269","article-title":"CellTalkDB: a manually curated database of ligand-receptor interactions in humans and mice","volume":"22","author":"Shao","year":"2021","journal-title":"Brief Bioinform"},{"key":"10.1016\/j.scib.2026.01.034_b0905","doi-asserted-by":"crossref","first-page":"966","DOI":"10.1038\/nmeth.4077","article-title":"Omnipath: guidelines and gateway for literature-curated signaling pathway resources","volume":"13","author":"T\u00fcrei","year":"2016","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0910","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkaf569","article-title":"MEBOCOST maps metabolite-mediated intercellular communications using single-cell RNA-seq","volume":"53","author":"Zheng","year":"2025","journal-title":"Nucleic Acids Res"},{"key":"10.1016\/j.scib.2026.01.034_b0915","doi-asserted-by":"crossref","first-page":"10934","DOI":"10.1093\/nar\/gkad841","article-title":"Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities","volume":"51","author":"Muller-Dott","year":"2023","journal-title":"Nucleic Acids Res"},{"key":"10.1016\/j.scib.2026.01.034_b0920","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1038\/s41592-019-0667-5","article-title":"NicheNet: modeling intercellular communication by linking ligands to target genes","volume":"17","author":"Browaeys","year":"2020","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b0925","doi-asserted-by":"crossref","unstructured":"Browaeys R, Gilis J, Sang-Aram C, et al. MultiNicheNet: a flexible framework for differential cell-cell communication analysis from multi-sample multi-condition single-cell transcriptomics data. bioRxiv 2023;2023.2006.2013.544751.","DOI":"10.1101\/2023.06.13.544751"},{"key":"10.1016\/j.scib.2026.01.034_b0930","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbad359","article-title":"Decoding functional cell-cell communication events by multi-view graph learning on spatial transcriptomics","volume":"24","author":"Li","year":"2023","journal-title":"Brief Bioinform"},{"key":"10.1016\/j.scib.2026.01.034_b0935","doi-asserted-by":"crossref","first-page":"1088","DOI":"10.1038\/s41467-021-21246-9","article-title":"Inference and analysis of cell-cell communication using CellChat","volume":"12","author":"Jin","year":"2021","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0940","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1038\/s41596-024-01045-4","article-title":"CellChat for systematic analysis of cell-cell communication from single-cell transcriptomics","volume":"20","author":"Jin","year":"2025","journal-title":"Nat Protoc"},{"key":"10.1016\/j.scib.2026.01.034_b0945","doi-asserted-by":"crossref","first-page":"1613","DOI":"10.1038\/s41556-024-01469-w","article-title":"LIANA+ provides an all-in-one framework for cell-cell communication inference","volume":"26","author":"Dimitrov","year":"2024","journal-title":"Nat Cell Biol"},{"key":"10.1016\/j.scib.2026.01.034_b0950","doi-asserted-by":"crossref","first-page":"4429","DOI":"10.1038\/s41467-022-32111-8","article-title":"Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data with SpaTalk","volume":"13","author":"Shao","year":"2022","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0955","doi-asserted-by":"crossref","first-page":"1744","DOI":"10.1016\/j.cell.2025.02.026","article-title":"Spatiotemporal modeling of molecular holograms","volume":"188","author":"Qiu","year":"2025","journal-title":"Cell"},{"key":"10.1016\/j.scib.2026.01.034_b0960","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbae347","article-title":"MetalinksDB: a flexible and contextualizable resource of metabolite-protein interactions","volume":"25","author":"Farr","year":"2024","journal-title":"Brief Bioinform"},{"key":"10.1016\/j.scib.2026.01.034_b0965","doi-asserted-by":"crossref","first-page":"2383","DOI":"10.1038\/s41596-025-01145-9","article-title":"Spatially resolved genome-wide joint profiling of epigenome and transcriptome with spatial-ATAC-RNA-seq and spatial-CUT&TAG-RNA-seq","volume":"20","author":"Li","year":"2025","journal-title":"Nat Protoc"},{"key":"10.1016\/j.scib.2026.01.034_b0970","doi-asserted-by":"crossref","first-page":"1261","DOI":"10.1038\/s41586-025-09478-x","article-title":"Spatial joint profiling of DNA methylome and transcriptome in tissues","volume":"646","author":"Lee","year":"2025","journal-title":"Nature"},{"key":"10.1016\/j.scib.2026.01.034_b0975","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1038\/s41586-020-03126-2","article-title":"Integrated spatial genomics reveals global architecture of single nuclei","volume":"590","author":"Takei","year":"2021","journal-title":"Nature"},{"key":"10.1016\/j.scib.2026.01.034_b0980","doi-asserted-by":"crossref","first-page":"1046","DOI":"10.1038\/s41587-023-01937-y","article-title":"Spatial multimodal analysis of transcriptomes and metabolomes in tissues","volume":"42","author":"Vicari","year":"2024","journal-title":"Nat Biotechnol"},{"key":"10.1016\/j.scib.2026.01.034_b0985","doi-asserted-by":"crossref","first-page":"872","DOI":"10.1038\/s41551-024-01205-7","article-title":"Spatial multi-omics at subcellular resolution via high-throughput in situ pairwise sequencing","volume":"8","author":"Wu","year":"2024","journal-title":"Nat Biomed Eng"},{"key":"10.1016\/j.scib.2026.01.034_b0990","doi-asserted-by":"crossref","first-page":"6048","DOI":"10.1038\/s41467-024-50308-x","article-title":"SANTO: a coarse-to-fine alignment and stitching method for spatial omics","volume":"15","author":"Li","year":"2024","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b0995","doi-asserted-by":"crossref","first-page":"2485","DOI":"10.1016\/j.cell.2024.03.029","article-title":"Integrative spatial analysis reveals a multi-layered organization of glioblastoma","volume":"187","author":"Greenwald","year":"2024","journal-title":"Cell"},{"key":"10.1016\/j.scib.2026.01.034_b1000","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1038\/s41586-023-05795-1","article-title":"Spatial epigenome-transcriptome co-profiling of mammalian tissues","volume":"616","author":"Zhang","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.scib.2026.01.034_b1005","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1038\/s41586-021-04217-4","article-title":"Spatial genomics enables multi-modal study of clonal heterogeneity in tissues","volume":"601","author":"Zhao","year":"2022","journal-title":"Nature"},{"key":"10.1016\/j.scib.2026.01.034_b1010","doi-asserted-by":"crossref","unstructured":"Jones MG, Sun D, Min KH, et al. Spatiotemporal lineage tracing reveals the dynamic spatial architecture of tumor growth and metastasis. bioRxiv 2024;2024.2010.2021.619529.","DOI":"10.1101\/2024.10.21.619529"},{"key":"10.1016\/j.scib.2026.01.034_b1015","doi-asserted-by":"crossref","first-page":"3035","DOI":"10.7150\/thno.102822","article-title":"Spatial metabolomics and transcriptomics reveal metabolic reprogramming and cellular interactions in nasopharyngeal carcinoma with high PD-1 expression and therapeutic response","volume":"15","author":"Ji","year":"2025","journal-title":"Theranostics"},{"key":"10.1016\/j.scib.2026.01.034_b1020","doi-asserted-by":"crossref","unstructured":"STAligner enables the integration and alignment of multiple spatial transcriptomics datasets enables the integration and alignment of multiple spatial transcriptomics datasets. Nat Comput Sci 2023; 3:831\u2013832.","DOI":"10.1038\/s43588-023-00543-x"},{"key":"10.1016\/j.scib.2026.01.034_b1025","doi-asserted-by":"crossref","unstructured":"Yang Y, Cui Y, Park S-J, et al. STAIG: spatial transcriptomics analysis via image-aided graph contrastive learning for domain exploration and alignment-free integration. bioRxiv 2023;2023.2012.2018.572279.","DOI":"10.1101\/2023.12.18.572279"},{"key":"10.1016\/j.scib.2026.01.034_b1030","doi-asserted-by":"crossref","first-page":"1123","DOI":"10.1038\/s42003-024-06814-1","article-title":"A graph self-supervised residual learning framework for domain identification and data integration of spatial transcriptomics","volume":"7","author":"Huang","year":"2024","journal-title":"Commun Biol"},{"key":"10.1016\/j.scib.2026.01.034_b1035","unstructured":"Gong Y, Yu Z. Rgast: relational graph attention network for spatial transcriptome analysis. bioRxiv 2024;2024.2008.2009.607420."},{"key":"10.1016\/j.scib.2026.01.034_b1040","doi-asserted-by":"crossref","first-page":"7603","DOI":"10.1038\/s41467-023-43220-3","article-title":"SPACEL: deep learning-based characterization of spatial transcriptome architectures","volume":"14","author":"Xu","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b1045","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1038\/s41592-022-01459-6","article-title":"Alignment and integration of spatial transcriptomics data","volume":"19","author":"Zeira","year":"2022","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b1050","first-page":"1124","article-title":"PASTE2: partial alignment of multi-slice spatially resolved transcriptomics data","volume":"33","author":"Liu","year":"2023","journal-title":"Genome Res"},{"key":"10.1016\/j.scib.2026.01.034_b1055","doi-asserted-by":"crossref","first-page":"8123","DOI":"10.1038\/s41467-023-43915-7","article-title":"STAlign: alignment of spatial transcriptomics data using diffeomorphic metric mapping","volume":"14","author":"Clifton","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b1060","doi-asserted-by":"crossref","first-page":"e42","DOI":"10.1093\/nar\/gkac150","article-title":"STRIDE: accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing","volume":"50","author":"Sun","year":"2022","journal-title":"Nucleic Acids Res"},{"key":"10.1016\/j.scib.2026.01.034_b1065","doi-asserted-by":"crossref","unstructured":"Wang G, Zhao J, Yan Y, et al. Construction of a 3D whole organism spatial atlas by joint modeling of multiple slices. bioRxiv 2023: 2023.2002.2002.526814.","DOI":"10.1101\/2023.02.02.526814"},{"key":"10.1016\/j.scib.2026.01.034_b1070","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1038\/s41467-023-35947-w","article-title":"Probabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with precast","volume":"14","author":"Liu","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b1075","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1186\/s13059-023-03078-6","article-title":"SPIRAL: integrating and aligning spatially resolved transcriptomics data across different experiments, conditions, and technologies","volume":"24","author":"Guo","year":"2023","journal-title":"Genome Biol"},{"key":"10.1016\/j.scib.2026.01.034_b1080","doi-asserted-by":"crossref","first-page":"7236","DOI":"10.1038\/s41467-023-43105-5","article-title":"Spatial-linked alignment tool (slat) for aligning heterogenous slices","volume":"14","author":"Xia","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b1085","doi-asserted-by":"crossref","first-page":"1658","DOI":"10.1038\/s41592-024-02316-4","article-title":"Deciphering spatial domains from spatial multi-omics with spatialglue","volume":"21","author":"Long","year":"2024","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b1090","doi-asserted-by":"crossref","first-page":"1061","DOI":"10.1016\/j.ccell.2025.03.017","article-title":"Spatial determinants of antibody-drug conjugate SHR-A1811 efficacy in neoadjuvant treatment for HER2-positive breast cancer","volume":"43","author":"Ma","year":"2025","journal-title":"Cancer Cell"},{"key":"10.1016\/j.scib.2026.01.034_b1095","doi-asserted-by":"crossref","first-page":"5687","DOI":"10.1038\/s41467-023-41349-9","article-title":"Multimodal spatiotemporal transcriptomic resolution of embryonic palate osteogenesis","volume":"14","author":"Pina","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b1100","doi-asserted-by":"crossref","DOI":"10.1016\/j.celrep.2022.111053","article-title":"Mesenchymal-epithelial interaction regulates gastrointestinal tract development in mouse embryos","volume":"40","author":"Zhao","year":"2022","journal-title":"Cell Rep"},{"key":"10.1016\/j.scib.2026.01.034_b1105","doi-asserted-by":"crossref","first-page":"976","DOI":"10.1016\/j.cell.2020.06.038","article-title":"Spatial transcriptomics and in situ sequencing to study alzheimer\u2019s disease","volume":"182","author":"Chen","year":"2020","journal-title":"Cell"},{"key":"10.1016\/j.scib.2026.01.034_b1110","doi-asserted-by":"crossref","first-page":"1390","DOI":"10.1038\/s41588-022-01157-1","article-title":"Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer","volume":"54","author":"Cui Zhou","year":"2022","journal-title":"Nat Genet"},{"key":"10.1016\/j.scib.2026.01.034_b1115","first-page":"D233","article-title":"SpatialDB: a database for spatially resolved transcriptomes","volume":"48","author":"Fan","year":"2020","journal-title":"Nucleic Acids Res"},{"key":"10.1016\/j.scib.2026.01.034_b1120","doi-asserted-by":"crossref","first-page":"D1053","DOI":"10.1093\/nar\/gkad933","article-title":"STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysis and visualization","volume":"52","author":"Xu","year":"2024","journal-title":"Nucleic Acids Res"},{"key":"10.1016\/j.scib.2026.01.034_b1125","doi-asserted-by":"crossref","first-page":"664","DOI":"10.1038\/s41592-025-02643-0","article-title":"Sharing data from the human tumor atlas network through standards, infrastructure and community engagement","volume":"22","author":"de Bruijn","year":"2025","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b1130","doi-asserted-by":"crossref","first-page":"1210","DOI":"10.1158\/0008-5472.CAN-23-2650","article-title":"The web-based portal spatialtme integrates histological images with single-cell and spatial transcriptomics to explore the tumor microenvironment","volume":"84","author":"Shi","year":"2024","journal-title":"Cancer Res"},{"key":"10.1016\/j.scib.2026.01.034_b1135","doi-asserted-by":"crossref","first-page":"1505","DOI":"10.1016\/j.jgg.2024.08.012","article-title":"CancerSRT: a spatially resolved transcriptomics database for human cancers","volume":"51","author":"Huo","year":"2024","journal-title":"J Genet Genomics"},{"key":"10.1016\/j.scib.2026.01.034_b1140","doi-asserted-by":"crossref","unstructured":"Li Y, Dennis S, Hutch MR, et al. Soar elucidates disease mechanisms and empowers drug discovery through spatial transcriptomics. bioRxiv 2023;2022.2004.2017.488596.","DOI":"10.1101\/2022.04.17.488596"},{"key":"10.1016\/j.scib.2026.01.034_b1145","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1038\/s41586-019-1629-x","article-title":"The human body at cellular resolution: the NIH human biomolecular atlas program","volume":"574","author":"Hu","year":"2019","journal-title":"Nature"},{"key":"10.1016\/j.scib.2026.01.034_b1150","doi-asserted-by":"crossref","first-page":"5700","DOI":"10.1038\/s41467-024-49846-1","article-title":"HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics","volume":"15","author":"Yuan","year":"2024","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b1155","doi-asserted-by":"crossref","first-page":"1505","DOI":"10.1038\/s41592-025-02721-3","article-title":"CellNEST reveals cell-cell relay networks using attention mechanisms on spatial transcriptomics","volume":"22","author":"Zohora","year":"2025","journal-title":"Nat Methods"},{"key":"10.1016\/j.scib.2026.01.034_b1160","doi-asserted-by":"crossref","first-page":"10259","DOI":"10.1038\/s41467-024-54710-3","article-title":"Spatially organized tumor-stroma boundary determines the efficacy of immunotherapy in colorectal cancer patients","volume":"15","author":"Feng","year":"2024","journal-title":"Nat Commun"},{"key":"10.1016\/j.scib.2026.01.034_b1165","doi-asserted-by":"crossref","DOI":"10.1126\/science.aaf7907","article-title":"Whole-organism lineage tracing by combinatorial and cumulative genome editing","volume":"353","author":"McKenna","year":"2016","journal-title":"Science"},{"key":"10.1016\/j.scib.2026.01.034_b1170","doi-asserted-by":"crossref","DOI":"10.1126\/science.abb3099","article-title":"Imaging cell lineage with a synthetic digital recording system","volume":"372","author":"Chow","year":"2021","journal-title":"Science"},{"key":"10.1016\/j.scib.2026.01.034_b1175","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1038\/s41586-022-04922-8","article-title":"A time-resolved, multi-symbol molecular recorder via sequential genome editing","volume":"608","author":"Choi","year":"2022","journal-title":"Nature"},{"key":"10.1016\/j.scib.2026.01.034_b1180","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1038\/s41587-023-01709-8","article-title":"Shoot the messenger: RNA editing is here","volume":"41","author":"Sheridan","year":"2023","journal-title":"Nat Biotechnol"},{"key":"10.1016\/j.scib.2026.01.034_b1185","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1146\/annurev-biochem-060208-105251","article-title":"Functions and regulation of RNA editing by ADAR deaminases","volume":"79","author":"Nishikura","year":"2010","journal-title":"Annu Rev Biochem"},{"key":"10.1016\/j.scib.2026.01.034_b1190","doi-asserted-by":"crossref","first-page":"1019","DOI":"10.1126\/science.aaq0180","article-title":"RNA editing with crispr-cas13","volume":"358","author":"Cox","year":"2017","journal-title":"Science"},{"key":"10.1016\/j.scib.2026.01.034_b1195","doi-asserted-by":"crossref","first-page":"2559","DOI":"10.1016\/j.cell.2022.05.013","article-title":"Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq","volume":"185","author":"Replogle","year":"2022","journal-title":"Cell"},{"key":"10.1016\/j.scib.2026.01.034_b1200","doi-asserted-by":"crossref","unstructured":"Wang H, He Y, Coelho PP, et al. Spatialagent: an autonomous AI agent for spatial biology. bioRxiv 2025;2025.2004.2003.646459.","DOI":"10.1101\/2025.04.03.646459"},{"key":"10.1016\/j.scib.2026.01.034_b1205","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1038\/s41565-023-01560-7","article-title":"Associating growth factor secretions and transcriptomes of single cells in nanovials using SEC-seq","volume":"19","author":"Udani","year":"2024","journal-title":"Nat Nanotechnol"}],"container-title":["Science Bulletin"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2095927326000411?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2095927326000411?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T09:44:36Z","timestamp":1778838276000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2095927326000411"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2]]},"references-count":240,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["S2095927326000411"],"URL":"https:\/\/doi.org\/10.1016\/j.scib.2026.01.034","relation":{},"ISSN":["2095-9273"],"issn-type":[{"value":"2095-9273","type":"print"}],"subject":[],"published":{"date-parts":[[2026,2]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Mapping biology in space: from spatial transcriptomics platforms to analytical tools and databases","name":"articletitle","label":"Article Title"},{"value":"Science Bulletin","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.scib.2026.01.034","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier B.V. and Science China Press.","name":"copyright","label":"Copyright"}]}}