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Animal cells are spatially organized as functional tissues where cellular gene expression data contain information that governs morphogenesis during the developmental process. Although several computational tissue reconstruction methods using transcriptomics data have been proposed, those methods have been ineffective in arranging cells in their correct positions in tissues or organs unless spatial information is explicitly provided.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>This study demonstrates stochastic self-organizing map clustering with Markov chain Monte Carlo calculations for optimizing informative genes effectively reconstruct any spatio\u2013temporal topology of cells from their transcriptome profiles with only a coarse topological guideline. The method, eSPRESSO (enhanced SPatial REconstruction by Stochastic Self-Organizing Map), provides a powerful in silico spatio\u2013temporal tissue reconstruction capability, as confirmed by using human embryonic heart and mouse embryo, brain, embryonic heart, and liver lobule with generally high reproducibility (average max. accuracy\u2009=\u200992.0%), while revealing topologically informative genes, or spatial discriminator genes. Furthermore, eSPRESSO was used for temporal analysis of human pancreatic organoids to infer rational developmental trajectories with several candidate \u2018temporal\u2019 discriminator genes responsible for various cell type differentiations.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>eSPRESSO provides a novel strategy for analyzing mechanisms underlying the spatio\u2013temporal formation of cellular organizations.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-023-05355-4","type":"journal-article","created":{"date-parts":[[2023,6,15]],"date-time":"2023-06-15T06:02:17Z","timestamp":1686808937000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["eSPRESSO: topological clustering of single-cell transcriptomics data to reveal informative genes for spatio\u2013temporal architectures of cells"],"prefix":"10.1186","volume":"24","author":[{"given":"Tomoya","family":"Mori","sequence":"first","affiliation":[]},{"given":"Toshiro","family":"Takase","sequence":"additional","affiliation":[]},{"given":"Kuan-Chun","family":"Lan","sequence":"additional","affiliation":[]},{"given":"Junko","family":"Yamane","sequence":"additional","affiliation":[]},{"given":"Cantas","family":"Alev","sequence":"additional","affiliation":[]},{"given":"Azuma","family":"Kimura","sequence":"additional","affiliation":[]},{"given":"Kenji","family":"Osafune","sequence":"additional","affiliation":[]},{"given":"Jun K.","family":"Yamashita","sequence":"additional","affiliation":[]},{"given":"Tatsuya","family":"Akutsu","sequence":"additional","affiliation":[]},{"given":"Hiroaki","family":"Kitano","sequence":"additional","affiliation":[]},{"given":"Wataru","family":"Fujibuchi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,6,15]]},"reference":[{"key":"5355_CR1","doi-asserted-by":"publisher","first-page":"1271","DOI":"10.1126\/science.aax1184","volume":"364","author":"MA Rossi","year":"2019","unstructured":"Rossi MA, Basiri ML, McHenry JA, Kosyk O, Otis JM, van den Munkhof HE, et al. 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