{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T07:30:10Z","timestamp":1775028610196,"version":"3.50.1"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T00:00:00Z","timestamp":1725408000000},"content-version":"vor","delay-in-days":41,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62394330"],"award-info":[{"award-number":["62394330"]}],"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":["62272361"],"award-info":[{"award-number":["62272361"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shaanxi Natural Science Funds for Distinguished Young Scholar","award":["2022JC-38"],"award-info":[{"award-number":["2022JC-38"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,25]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Recent advances in spatial transcriptomics (ST) enable measurements of transcriptome within intact biological tissues by preserving spatial information, offering biologists unprecedented opportunities to comprehensively understand tissue micro-environment, where spatial domains are basic units of tissues. Although great efforts are devoted to this issue, they still have many shortcomings, such as ignoring local information and relations of spatial domains, requiring alternatives to solve these problems. Here, a novel algorithm for spatial domain identification in Spatial Transcriptomics data with Structure Correlation and Self-Representation (ST-SCSR), which integrates local information, global information, and similarity of spatial domains. Specifically, ST-SCSR utilzes matrix tri-factorization to simultaneously decompose expression profiles and spatial network of spots, where expressional and spatial features of spots are fused via the shared factor matrix that interpreted as similarity of spatial domains. Furthermore, ST-SCSR learns affinity graph of spots by manipulating expressional and spatial features, where local preservation and sparse constraints are employed, thereby enhancing the quality of graph. The experimental results demonstrate that ST-SCSR not only outperforms state-of-the-art algorithms in terms of accuracy, but also identifies many potential interesting patterns.<\/jats:p>","DOI":"10.1093\/bib\/bbae437","type":"journal-article","created":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T23:40:50Z","timestamp":1725493250000},"source":"Crossref","is-referenced-by-count":6,"title":["ST-SCSR: identifying spatial domains in spatial transcriptomics data via structure correlation and self-representation"],"prefix":"10.1093","volume":"25","author":[{"given":"Min","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Xidian University , No. 2 South Taibai Road, 710071 Xi\u2019an Shaanxi , China"},{"name":"Key Laboratory of Smart Human-Computer Interaction and Wearable Technology of Shaanxi Province, Xidian University , No. 2 South Taibai Road, 710071 Xi\u2019an Shaanxi , China"}]},{"given":"Wensheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Cyber Engineering, GuangZhou University , No. 230 Wai Huan Xi Road,Guangzhou Higher Education Mega Center, 510006 Guangzhou Guangdong , China"}]},{"given":"Xiaoke","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xidian University , No. 2 South Taibai Road, 710071 Xi\u2019an Shaanxi , China"},{"name":"Key Laboratory of Smart Human-Computer Interaction and Wearable Technology of Shaanxi Province, Xidian University , No. 2 South Taibai Road, 710071 Xi\u2019an Shaanxi , China"}]}],"member":"286","published-online":{"date-parts":[[2024,9,4]]},"reference":[{"key":"2024090406274220500_ref1","doi-asserted-by":"crossref","first-page":"912","DOI":"10.1038\/s41592-021-01196-2","article-title":"An unsupervised method for physical cell interaction profiling of complex 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