{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T21:58:46Z","timestamp":1790805526884,"version":"4.1.0"},"reference-count":37,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T00:00:00Z","timestamp":1787616000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100014989","name":"The Chan Zuckerberg Initiative","doi-asserted-by":"publisher","award":["2019-198110 (5022)"],"award-info":[{"award-number":["2019-198110 (5022)"]}],"id":[{"id":"10.13039\/100014989","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P30 CA008748"],"award-info":[{"award-number":["P30 CA008748"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["R01GM152927"],"award-info":[{"award-number":["R01GM152927"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["cell.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Cell Reports Methods"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.crmeth.2026.101606","type":"journal-article","created":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T15:32:57Z","timestamp":1790263977000},"page":"101606","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["A single-cell spatiotemporal manifold of tissue morphology and dynamics"],"prefix":"10.1016","author":[{"given":"Erin","family":"Haus","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5696-0591","authenticated-orcid":false,"given":"Anthony","family":"Santella","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yichi","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruohan","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dali","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhirong","family":"Bao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.crmeth.2026.101606_bib1","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/j.cell.2013.11.046","article-title":"De novo inference of systems-level mechanistic models of development from live-imaging-based phenotype analysis","volume":"156","author":"Du","year":"2014","journal-title":"Cell"},{"key":"10.1016\/j.crmeth.2026.101606_bib2","doi-asserted-by":"crossref","first-page":"5753","DOI":"10.1038\/s41467-019-13625-0","article-title":"Multi-scale imaging and analysis identify pan-embryo cell dynamics of germlayer formation in zebrafish","volume":"10","author":"Shah","year":"2019","journal-title":"Nat. Commun."},{"key":"10.1016\/j.crmeth.2026.101606_bib3","doi-asserted-by":"crossref","first-page":"859","DOI":"10.1016\/j.cell.2018.09.031","article-title":"In Toto Imaging and Reconstruction of Post-Implantation Mouse Development at the Single-Cell Level","volume":"175","author":"McDole","year":"2018","journal-title":"Cell"},{"key":"10.1016\/j.crmeth.2026.101606_bib4","doi-asserted-by":"crossref","first-page":"772","DOI":"10.1038\/s41586-023-06548-w","article-title":"Single-cell, whole-embryo phenotyping of mammalian developmental disorders","volume":"623","author":"Huang","year":"2023","journal-title":"Nature"},{"key":"10.1016\/j.crmeth.2026.101606_bib5","doi-asserted-by":"crossref","first-page":"2612","DOI":"10.1016\/j.jmb.2018.06.018","article-title":"Microscopy in Infectious Disease Research-Imaging Across Scales","volume":"430","author":"Laketa","year":"2018","journal-title":"J. Mol. Biol."},{"key":"10.1016\/j.crmeth.2026.101606_bib6","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1038\/s41592-021-01308-y","article-title":"MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging","volume":"19","author":"Schapiro","year":"2022","journal-title":"Nat. Methods"},{"key":"10.1016\/j.crmeth.2026.101606_bib7","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1038\/s41592-023-02124-2","article-title":"Unsupervised and supervised discovery of tissue cellular neighborhoods from cell phenotypes","volume":"21","author":"Hu","year":"2024","journal-title":"Nat. Methods"},{"key":"10.1016\/j.crmeth.2026.101606_bib8","doi-asserted-by":"crossref","first-page":"7991","DOI":"10.1038\/s41467-025-63140-8","article-title":"DECIPHER for learning disentangled cellular embeddings in large-scale heterogeneous spatial omics data","volume":"16","author":"Xia","year":"2025","journal-title":"Nat. Commun."},{"key":"10.1016\/j.crmeth.2026.101606_bib9","doi-asserted-by":"crossref","first-page":"2000","DOI":"10.1038\/s41592-023-02083-8","article-title":"Uncovering developmental time and tempo using deep learning","volume":"20","author":"Toulany","year":"2023","journal-title":"Nat. Methods"},{"key":"10.1016\/j.crmeth.2026.101606_bib10","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1038\/s42256-024-00801-1","article-title":"Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology","volume":"6","author":"Bonazzola","year":"2024","journal-title":"Nat. Mach. Intell."},{"key":"10.1016\/j.crmeth.2026.101606_bib11","doi-asserted-by":"crossref","DOI":"10.7554\/eLife.77918","article-title":"Cross-modality synthesis of EM time series and live fluorescence imaging","volume":"11","author":"Santella","year":"2022","journal-title":"eLife"},{"key":"10.1016\/j.crmeth.2026.101606_bib12","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.crmeth.2026.101606_bib13","first-page":"11492","article-title":"LiDAR-based Online 3D Video Object Detection with Graph-based Message Passing and Spatiotemporal Transformer Attention","author":"Yin","year":"2020","journal-title":"Proc. CVPR. IEEE"},{"key":"10.1016\/j.crmeth.2026.101606_bib14","first-page":"19594","article-title":"Space-time Mixing Attention for Video Transformer","volume":"34","author":"Bulat","year":"2021","journal-title":"Adv Neur"},{"key":"10.1016\/j.crmeth.2026.101606_bib15","series-title":"ViViT: A Video Vision Transformer","first-page":"6816","author":"Arnab","year":"2021"},{"key":"10.1016\/j.crmeth.2026.101606_bib16","first-page":"813","article-title":"Is space-time attention all you need for video understanding? Proceedings of the 38th International Conference on Machine Learning","volume":"139","author":"Bertasius","year":"2021","journal-title":"PMLR"},{"key":"10.1016\/j.crmeth.2026.101606_bib17","first-page":"26192","article-title":"SEAL: Semantic Attention Learning for Long Video Representation","author":"Wang","year":"2025","journal-title":"Proc. CVPR. IEEE"},{"key":"10.1016\/j.crmeth.2026.101606_bib18","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1038\/s41592-025-02983-x","article-title":"MultiCell: geometric learning in multicellular development","volume":"23","author":"Yang","year":"2026","journal-title":"Nat. Methods"},{"key":"10.1016\/j.crmeth.2026.101606_bib19","doi-asserted-by":"crossref","DOI":"10.7554\/eLife.66410","article-title":"Fast deep neural correspondence for tracking and identifying neurons in C. elegans using semi-synthetic training","volume":"10","author":"Yu","year":"2021","journal-title":"eLife"},{"key":"10.1016\/j.crmeth.2026.101606_bib20","doi-asserted-by":"crossref","first-page":"225","DOI":"10.4236\/jbise.2018.118018","article-title":"An Observation Data Driven Simulation and Analysis Framework for Early Stage C. elegans Embryogenesis","volume":"11","author":"Wang","year":"2018","journal-title":"J. Biomed. Sci. Eng."},{"key":"10.1016\/j.crmeth.2026.101606_bib21","doi-asserted-by":"crossref","first-page":"7426","DOI":"10.1073\/pnas.0500334102","article-title":"Geometric diffusions as a tool for harmonic analysis and structure definition of data: diffusion maps","volume":"102","author":"Coifman","year":"2005","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"10.1016\/j.crmeth.2026.101606_bib22","doi-asserted-by":"crossref","first-page":"3266","DOI":"10.1242\/dev.096040","article-title":"Systematic quantification of developmental phenotypes at single-cell resolution during embryogenesis","volume":"140","author":"Moore","year":"2013","journal-title":"Development"},{"key":"10.1016\/j.crmeth.2026.101606_bib23","doi-asserted-by":"crossref","first-page":"893","DOI":"10.1038\/s41592-021-01216-1","article-title":"A 4D single-cell protein atlas of transcription factors delineates spatiotemporal patterning during embryogenesis","volume":"18","author":"Ma","year":"2021","journal-title":"Nat. Methods"},{"key":"10.1016\/j.crmeth.2026.101606_bib24","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/0012-1606(83)90201-4","article-title":"The embryonic cell lineage of the nematode Caenorhabditis elegans","volume":"100","author":"Sulston","year":"1983","journal-title":"Dev. Biol."},{"key":"10.1016\/j.crmeth.2026.101606_bib25","article-title":"Rapid canalization of chromosome conformation-transcription fingerprints during embryogenesis revealed by fully-automated cell identity decoding with CeSCALE","author":"Ntemos","year":"2025","journal-title":"bioRxiv"},{"key":"10.1016\/j.crmeth.2026.101606_bib26","article-title":"Unifying community whole-brain imaging datasets enables robust neuron identification and reveals determinants of neuron position in C. elegans","volume":"5","author":"Sprague","year":"2025","journal-title":"Cell Rep. Methods"},{"key":"10.1016\/j.crmeth.2026.101606_bib27","doi-asserted-by":"crossref","first-page":"592","DOI":"10.1016\/j.devcel.2015.07.014","article-title":"The Regulatory Landscape of Lineage Differentiation in a Metazoan Embryo","volume":"34","author":"Du","year":"2015","journal-title":"Dev. Cell"},{"key":"10.1016\/j.crmeth.2026.101606_bib28","doi-asserted-by":"crossref","first-page":"2707","DOI":"10.1073\/pnas.0511111103","article-title":"Automated cell lineage tracing in Caenorhabditis elegans","volume":"103","author":"Bao","year":"2006","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"10.1016\/j.crmeth.2026.101606_bib29","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1186\/1471-2105-15-217","article-title":"A semi-local neighborhood-based framework for probabilistic cell lineage tracing","volume":"15","author":"Santella","year":"2014","journal-title":"BMC Bioinf."},{"key":"10.1016\/j.crmeth.2026.101606_bib30","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1534\/genetics.111.129486","article-title":"Overcoming redundancy: an RNAi enhancer screen for morphogenesis genes in Caenorhabditis elegans","volume":"188","author":"Sawyer","year":"2011","journal-title":"Genetics"},{"key":"10.1016\/j.crmeth.2026.101606_bib31","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pgen.1010319","article-title":"Zyxin contributes to coupling between cell junctions and contractile actomyosin networks during apical constriction","volume":"19","author":"Slabodnick","year":"2023","journal-title":"PLoS Genet."},{"key":"10.1016\/j.crmeth.2026.101606_bib32","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1038\/s41586-024-07441-w","article-title":"A whole-slide foundation model for digital pathology from real-world data","volume":"630","author":"Xu","year":"2024","journal-title":"Nature"},{"key":"10.1016\/j.crmeth.2026.101606_bib33","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1038\/s41586-024-07618-3","article-title":"A multimodal generative AI copilot for human pathology","volume":"634","author":"Lu","year":"2024","journal-title":"Nature"},{"key":"10.1016\/j.crmeth.2026.101606_bib34","article-title":"Signature verification using a\u201d siamese\u201d time delay neural network","volume":"6","author":"Bromley","year":"1993","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.crmeth.2026.101606_bib35","article-title":"Neighbourhood consensus networks","volume":"31","author":"Rocco","year":"2018","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.crmeth.2026.101606_bib36","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1186\/1471-2105-7-275","article-title":"AceTree: a tool for visual analysis of Caenorhabditis elegans embryogenesis","volume":"7","author":"Boyle","year":"2006","journal-title":"BMC Bioinf."},{"key":"10.1016\/j.crmeth.2026.101606_bib37","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1186\/s12859-018-2127-0","article-title":"AceTree: a major update and case study in the long term maintenance of open-source scientific software","volume":"19","author":"Katzman","year":"2018","journal-title":"BMC Bioinf."}],"container-title":["Cell Reports Methods"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2667237526003073?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2667237526003073?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T21:06:48Z","timestamp":1790802408000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2667237526003073"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":37,"alternative-id":["S2667237526003073"],"URL":"https:\/\/doi.org\/10.1016\/j.crmeth.2026.101606","relation":{},"ISSN":["2667-2375"],"issn-type":[{"value":"2667-2375","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A single-cell spatiotemporal manifold of tissue morphology and dynamics","name":"articletitle","label":"Article Title"},{"value":"Cell Reports Methods","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.crmeth.2026.101606","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 Inc.","name":"copyright","label":"Copyright"}],"article-number":"101606"}}