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学习笔记,仅供参考,有错必纠
博客阅读索引:博客阅读及知识获取指南
文章目录
-
- A comprehensive comparison on cell-type composition inference for spatial transcriptomics data
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- Abstract
- Introduction
- Computational methods developed for cell-type deconvolution of ST data
- Benchmarking ST deconvolution methods performance
- 文中重要图表
A comprehensive comparison on cell-type composition inference for spatial transcriptomics data
Author:Jiawen Chen, Weifang Liu, Tianyou Luo, et al.
Journal:Briefings in Bioinformatics
Year:2022
DOI:10.1093/bib/bbac245
Keywords:spatial transcriptomics, single-cell, cell-type deconvolution, deep learning, probabilistic modeling
Code:9 in the paper
Abstract
空间转录组学(ST)技术使研究人员能够在保持位置信息的同时检查转录情况.
学习笔记,仅供参考,有错必纠
博客阅读索引:博客阅读及知识获取指南
文章目录
-
- A comprehensive comparison on cell-type composition inference for spatial transcriptomics data
-
- Abstract
- Introduction
- Computational methods developed for cell-type deconvolution of ST data
- Benchmarking ST deconvolution methods performance
- 文中重要图表
A comprehensive comparison on cell-type composition inference for spatial transcriptomics data
Author:Jiawen Chen, Weifang Liu, Tianyou Luo, et al.
Journal:Briefings in Bioinformatics
Year:2022
DOI:10.1093/bib/bbac245
Keywords:spatial transcriptomics, single-cell, cell-type deconvolution, deep learning, probabilistic modeling
Code:9 in the paper
Abstract
空间转录组学(ST)技术使研究人员能够在保持位置信息的同时检查转录情况.
本文标签: 单细胞论文ComprehensiveComparisoncell
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