{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T18:01:28Z","timestamp":1790704888469,"version":"4.1.0"},"update-to":[{"DOI":"10.1371\/journal.pbio.3003690","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000}}],"reference-count":39,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T00:00:00Z","timestamp":1789516800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012476","name":"Fundamental Research Funds for Central Universities of the Central South University","doi-asserted-by":"publisher","award":["2026JBMC007"],"award-info":[{"award-number":["2026JBMC007"]}],"id":[{"id":"10.13039\/501100012476","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62673041"],"award-info":[{"award-number":["62673041"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosbiology.org"],"crossmark-restriction":false},"short-container-title":["PLoS Biol"],"abstract":"<jats:p>\n                    Recent advances in spatial multi-omics technologies have opened new avenues for characterizing tissue architecture and function in situ, by simultaneously providing multimodal and complementary information\u2014such as spatially resolved transcriptomic, epigenomic, and proteomic features. Current computational approaches face substantial challenges, such as effective integration of multi-omics molecular information with spatial information and corresponding high-resolution histology images. To address this challenge, we proposed SpaMOAL (\n                    <jats:bold>Spa<\/jats:bold>\n                    tially\n                    <jats:bold>M<\/jats:bold>\n                    ulti-\n                    <jats:bold>O<\/jats:bold>\n                    mics graph contr\n                    <jats:bold>A<\/jats:bold>\n                    stive\n                    <jats:bold>L<\/jats:bold>\n                    earning), a graph-based contrastive learning approach for spatial domain identification. SpaMOAL learns clustering-friendly representations from spatial multi-omics data by integrating spatial coordinates, histological image features, and molecular profiles, enabling accurate delineation of spatial tissue domains. Benchmarking across multiple recent paired spatial multi-omics datasets from mouse and human demonstrated that SpaMOAL consistently outperforms existing methods. By enabling accurate spatial domain delineation, SpaMOAL provides a powerful framework for interpreting tissue organization and cellular microenvironments.\n                  <\/jats:p>","DOI":"10.1371\/journal.pbio.3003690","type":"journal-article","created":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T17:49:18Z","timestamp":1789580958000},"page":"e3003690","update-policy":"https:\/\/doi.org\/10.1371\/journal.pbio.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["SpaMOAL is a deep learning method that enables accurate spatial domain identification from multi-omics data"],"prefix":"10.1371","volume":"24","author":[{"given":"Jinxia","family":"Wang","sequence":"first","affiliation":[{"name":"Beijing Jiaotong University","place":["Beijing, China"],"department":["School of Software Engineering"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuying","family":"Huo","sequence":"additional","affiliation":[{"name":"Peking University Health 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