Interpretable machine learning-guided single-cell mapping deciphers multi-lineage pancreatic dysregulation in type 2 diabetes.
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| Title: | Interpretable machine learning-guided single-cell mapping deciphers multi-lineage pancreatic dysregulation in type 2 diabetes. |
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| Authors: | Xie X; Department of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China., Wu C; Department of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China., Yang Y; Department of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China., Su W; Department of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China., Dao F; School of Biological Sciences, Nanyang Technological University, Singapore, 639798, Singapore., Huang J; Department of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China., Shi Z; Clinical Genetics Laboratory, Clinical Medical College & Affiliated Hospital, Chengdu University, Chengdu, 610106, China., Lyu H; Department of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China. hao.lyu@uestc.edu.cn., Lin H; Department of Clinical Laboratory, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China. hlin@uestc.edu.cn. |
| Source: | Cardiovascular diabetology [Cardiovasc Diabetol] 2025 Jul 24; Vol. 24 (1), pp. 300. Date of Electronic Publication: 2025 Jul 24. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 101147637 Publication Model: Electronic Cited Medium: Internet ISSN: 1475-2840 (Electronic) Linking ISSN: 14752840 NLM ISO Abbreviation: Cardiovasc Diabetol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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