中文版 | English
CSpace
Single-cell technologies: From research to application
Wen, Lu1; Li, Guoqiang1; Huang, Tao2; Geng, Wei3; Pei, Hao4; Yang, Jialiang5; Zhu, Miao6; Zhang, Pengfei7; Hou, Rui5; Tian, Geng5
2022-11-08
摘要In recent years, more and more single-cell technologies have been devel-oped. A vast amount of single-cell omics data has been generated by large projects, such as the Human Cell Atlas, the Mouse Cell Atlas, the Mouse RNA Atlas, the Mouse ATAC Atlas, and the Plant Cell Atlas. Based on these single-cell big data, thousands of bioinformatics algorithms for quality con-trol, clustering, cell-type annotation, developmental inference, cell-cell tran-sition, cell-cell interaction, and spatial analysis are developed. With powerful experimental single-cell technology and state-of-the-art big data analysis methods based on artificial intelligence, the molecular landscape at the sin-gle-cell level can be revealed. With spatial transcriptomics and single-cell multi-omics, even the spatial dynamic multi-level regulatory mechanisms can be deciphered. Such single-cell technologies have many successful ap-plications in oncology, assisted reproduction, embryonic development, and plant breeding. We not only review the experimental and bioinformatics methods for single-cell research, but also discuss their applications in various fields and forecast the future directions for single-cell technologies. We believe that spatial transcriptomics and single-cell multi-omics will become the next booming business for mechanism research and commer-cial industry.
DOI10.1016/j.xinn.2022.100342
发表期刊INNOVATION-THE EUROPEAN JOURNAL OF SOCIAL SCIENCE RESEARCH
ISSN1351-1610
卷号3期号:6页码:17
通讯作者Zhao, Yunlong(yunlong.zhao@surrey.ac.uk) ; Cao, Xin(caox@fudan.edu.cn) ; Peng, Guangdun(peng_guangdun@gibh.ac.cn) ; Ren, Xianwen(renxwise@pku.edu.cn) ; Jiang, Nan(jiangnansophia@scu.edu.cn) ; Tian, Caihuan(tiancaihuan@caas.cn) ; Chen, Zi-Jiang(chenzijiang@hotmail.com)
收录类别SCI
WOS记录号WOS:000883049100005
语种英语