Integration of Computational Analysis and Spatial Transcriptomics in Single-cell Studies

IF 11.5 2区 生物学 Q1 GENETICS & HEREDITY
Ran Wang , Guangdun Peng , Patrick P.L. Tam , Naihe Jing
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引用次数: 9

Abstract

Recent advances of single-cell transcriptomics technologies and allied computational methodologies have revolutionized molecular cell biology. Meanwhile, pioneering explorations in spatial transcriptomics have opened up avenues to address fundamental biological questions in health and diseases. Here, we review the technical attributes of single-cell RNA sequencing and spatial transcriptomics, and the core concepts of computational data analysis. We further highlight the challenges in the application of data integration methodologies and the interpretation of the biological context of the findings.

Abstract Image

Abstract Image

计算分析与空间转录组学在单细胞研究中的整合
单细胞转录组学技术和相关计算方法的最新进展彻底改变了分子细胞生物学。与此同时,空间转录组学的开创性探索为解决健康和疾病中的基本生物学问题开辟了途径。在这里,我们回顾了单细胞RNA测序和空间转录组学的技术属性,以及计算数据分析的核心概念。我们进一步强调了数据整合方法的应用和对研究结果生物学背景的解释方面的挑战。
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来源期刊
Genomics, Proteomics & Bioinformatics
Genomics, Proteomics & Bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
14.30
自引率
4.20%
发文量
844
审稿时长
61 days
期刊介绍: Genomics, Proteomics and Bioinformatics (GPB) is the official journal of the Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China. It aims to disseminate new developments in the field of omics and bioinformatics, publish high-quality discoveries quickly, and promote open access and online publication. GPB welcomes submissions in all areas of life science, biology, and biomedicine, with a focus on large data acquisition, analysis, and curation. Manuscripts covering omics and related bioinformatics topics are particularly encouraged. GPB is indexed/abstracted by PubMed/MEDLINE, PubMed Central, Scopus, BIOSIS Previews, Chemical Abstracts, CSCD, among others.
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