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scStateDynamics: deciphering the drug-responsive tumor cell state dynamics by modeling single-cell level expression changes.

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Title: scStateDynamics: deciphering the drug-responsive tumor cell state dynamics by modeling single-cell level expression changes.
Authors: Guo W; MOE Key Lab of Bioinformatics, Department of Automation, BNRIST Bioinformatics Division, Tsinghua University, Beijing, China., Li X; MOE Key Lab of Bioinformatics, Department of Automation, BNRIST Bioinformatics Division, Tsinghua University, Beijing, China., Wang D; Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China., Yan N; MOE Key Lab of Bioinformatics, Department of Automation, BNRIST Bioinformatics Division, Tsinghua University, Beijing, China., Hu Q; MOE Key Lab of Bioinformatics, Department of Automation, BNRIST Bioinformatics Division, Tsinghua University, Beijing, China., Yang F; AI Lab, Shenzhen, Tencent, China., Zhang X; MOE Key Lab of Bioinformatics, Department of Automation, BNRIST Bioinformatics Division, Tsinghua University, Beijing, China.; Center for Synthetic and Systems Biology, School of Life Sciences and School of Medicine, Tsinghua University, Beijing, China., Yao J; AI Lab, Shenzhen, Tencent, China. jianhuayao@tencent.com., Gu J; MOE Key Lab of Bioinformatics, Department of Automation, BNRIST Bioinformatics Division, Tsinghua University, Beijing, China. jgu@tsinghua.edu.cn.
Source: Genome biology [Genome Biol] 2024 Nov 21; Vol. 25 (1), pp. 297. Date of Electronic Publication: 2024 Nov 21.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: BioMed Central Ltd Country of Publication: England NLM ID: 100960660 Publication Model: Electronic Cited Medium: Internet ISSN: 1474-760X (Electronic) Linking ISSN: 14747596 NLM ISO Abbreviation: Genome Biol Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:1474-760X
DOI:10.1186/s13059-024-03436-y