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SECTOR: structural entropy-based learning of spatiotemporal organisation in spatial transcriptomics.

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Title: SECTOR: structural entropy-based learning of spatiotemporal organisation in spatial transcriptomics.
Authors: Huang L; State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Suzhou, 215123, China., Zhang J; School of Cyber Science and Technology, Beihang University, Beijing, 100191, China., Gong W; State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Suzhou, 215123, China., Zeng G; School of Computer Science and Engineering, Beihang University, Beijing, 100191, China., Peng H; School of Cyber Science and Technology, Beihang University, Beijing, 100191, China., Chen D; State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Suzhou, 215123, China.
Source: Bioinformatics (Oxford, England) [Bioinformatics] 2026 Jun 01; Vol. 42 (6).
Publication Type: Journal Article
Journal Info: Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Huang+L%22">Huang L</searchLink>; State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Suzhou, 215123, China.<br /><searchLink fieldCode="AU" term="%22Zhang+J%22">Zhang J</searchLink>; School of Cyber Science and Technology, Beihang University, Beijing, 100191, China.<br /><searchLink fieldCode="AU" term="%22Gong+W%22">Gong W</searchLink>; State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Suzhou, 215123, China.<br /><searchLink fieldCode="AU" term="%22Zeng+G%22">Zeng G</searchLink>; School of Computer Science and Engineering, Beihang University, Beijing, 100191, China.<br /><searchLink fieldCode="AU" term="%22Peng+H%22">Peng H</searchLink>; School of Cyber Science and Technology, Beihang University, Beijing, 100191, China.<br /><searchLink fieldCode="AU" term="%22Chen+D%22">Chen D</searchLink>; State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Suzhou, 215123, China.
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  Data: <searchLink fieldCode="JN" term="%229808944%22">Bioinformatics (Oxford, England)</searchLink> [Bioinformatics] 2026 Jun 01; Vol. 42 (6).
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Oxford+University+Press%22">Oxford University Press </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>9808944 <i>Publication Model: </i>Print <i>Cited Medium: </i>Internet <i>ISSN: </i>1367-4811 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2213674803%22">13674803 </searchLink><i>NLM ISO Abbreviation: </i>Bioinformatics <i>Subsets: </i>MEDLINE
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        Value: 10.1093/bioinformatics/btag367
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              Text: 2026 Jun 01
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