{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T00:15:34Z","timestamp":1789690534540,"version":"4.0.1"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"9","license":[{"start":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T00:00:00Z","timestamp":1787788800000},"content-version":"vor","delay-in-days":0,"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":["12501693"],"award-info":[{"award-number":["12501693"]}],"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":["12571528"],"award-info":[{"award-number":["12571528"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Guangdong Province, China","award":["2025A1515011685"],"award-info":[{"award-number":["2025A1515011685"]}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2025YFE0113400"],"award-info":[{"award-number":["2025YFE0113400"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,8,31]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Multi-timepoint spatial transcriptomics enables study of developmental processes in native tissue context, but cell-state mixtures within spots and lack of direct spatial correspondence across sections complicate trajectory inference and biological interpretation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>st2traj is a deconvolution-informed trajectory framework using spot-state composition for multi-timepoint spatial trajectory inference. In a human heart pseudo-spot benchmark, DECODE showed competitive and balanced performance among five deconvolution methods. In multi-timepoint human heart data, unscaled DECODE-derived proportions produced smoother trajectory fields and stronger agreement with expression-derived marker programs than normalized spot-level expression. st2traj also showed greater spatial coherence than spaTrack, while exploratory comparisons with moscot and CASCAT revealed complementary method-specific strengths. Application to an independent chicken heart dataset recovered stage-associated trajectory changes across D7, D10, and D14.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and Implementation<\/jats:title>\n                    <jats:p>Source code: https:\/\/github.com\/xiaoxiaoxier\/st2traj. Software v0.1.0 and processed data are archived at Zenodo: https:\/\/doi.org\/10.5281\/zenodo.21487030 and https:\/\/doi.org\/10.5281\/zenodo.21502094.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btag645","type":"journal-article","created":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T13:27:17Z","timestamp":1787837237000},"source":"Crossref","is-referenced-by-count":0,"title":["<tt>st2traj<\/tt>\n                    : deconvolution-informed trajectory inference for multi-timepoint spatial transcriptomics"],"prefix":"10.1093","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7076-8432","authenticated-orcid":false,"given":"Zhuo","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Computational Mathematics and Cybernetics, Shenzhen MSU\u2013BIT University , Shenzhen, Guangdong 518172,","place":["P.R. 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