Recovering single-cell expression profiles from spatial transcriptomics with scResolve.
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| Title: | Recovering single-cell expression profiles from spatial transcriptomics with scResolve. |
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| Authors: | Chen H; Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA., Lee YJ; Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA., Ovando-Ricardez JA; Dorothy M. Davis Heart and Lung Research Institute, Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, The Ohio State University, Columbus, OH 43210, USA., Rosas L; Dorothy M. Davis Heart and Lung Research Institute, Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, The Ohio State University, Columbus, OH 43210, USA., Rojas M; Dorothy M. Davis Heart and Lung Research Institute, Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, The Ohio State University, Columbus, OH 43210, USA., Mora AL; Dorothy M. Davis Heart and Lung Research Institute, Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, The Ohio State University, Columbus, OH 43210, USA., Bar-Joseph Z; Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA., Lugo-Martinez J; Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA. Electronic address: jlugomar@andrew.cmu.edu. |
| Source: | Cell reports methods [Cell Rep Methods] 2024 Oct 21; Vol. 4 (10), pp. 100864. Date of Electronic Publication: 2024 Sep 25. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Elsevier Inc Country of Publication: United States NLM ID: 9918227360606676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2667-2375 (Electronic) Linking ISSN: 26672375 NLM ISO Abbreviation: Cell Rep Methods Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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