Single-cell technologies : From research to application
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
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Detail(s)
Original language | English |
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Article number | 100342 |
Journal / Publication | The Innovation |
Volume | 3 |
Issue number | 6 |
Online published | 18 Oct 2022 |
Publication status | Published - 8 Nov 2022 |
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DOI | DOI |
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Attachment(s) | Documents
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Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85143751221&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(8704f59c-df99-41a5-85ff-d39c81f32f0e).html |
Abstract
In recent years, more and more single-cell technologies have been developed. 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 control, clustering, cell-type annotation, developmental inference, cell-cell transition, 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 single-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 applications 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 commercial industry.
Research Area(s)
- GENOME-WIDE EXPRESSION, MOUSE EARLY EMBRYOS, GENE-EXPRESSION, RNA-SEQ, CHROMATIN ACCESSIBILITY, TRANSCRIPTOME ATLAS, METHYLOME LANDSCAPES, STOMATAL LINEAGE, STEM-CELLS, REVEALS
Citation Format(s)
Single-cell technologies : From research to application. / Wen, Lu; Li, Guoqiang; Huang, Tao et al.
In: The Innovation, Vol. 3, No. 6, 100342, 08.11.2022.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
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