Single-Cell Genomics: Technical Advancements and Biological Applications
A special issue of BioTech (ISSN 2673-6284).
Deadline for manuscript submissions: closed (15 December 2020) | Viewed by 313
Special Issue Editors
Interests: microarrays; next generation sequencing; genomics; genomics technologies; gene expression; RNA-seq; translational research
Special Issues, Collections and Topics in MDPI journals
Interests: translational research; lung disease; genomics technologies; microarrays; next generation sequencing; RNA-seq; gene expression
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Over the past 20 years, many different -omics technologies have been created that allow researchers to globally measure molecular features of biological and clinical samples. More recent unprecedented advances in molecular biology and cell isolation techniques have permitted the sequencing of the minute amounts of DNA and RNA present in a single cell. This approach allows for insight into the heterogeneity of tissues and organs in normal development and function as well as in disease processes and improves our understanding of the functions of each individual cell in the context of its microenvironment. Single-cell RNA-seq and single-nucleus RNA-seq are becoming more and more routine, despite certain challenges and high costs. We also observe that technological development is shifting to other modalities: DNA, protein, chromatin modifications, and more. This issue will cover research on all aspects of single-cell -omics, including novel method development (both wet-lab and bioinformatics) that add value to our understanding of developmental and disease processes with single-cell granularity and hopefully on translational research, accelerating the move of single-cell -omics advancements into pharma and clinic.
Dr. Yuriy Alekseyev
Dr. Gang Liu
Guest Editors
Manuscript Submission Information
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Keywords
- single-cell RNA-seq
- single-nucleus RNA-seq
- single-cell ATAC-seq
- single-cell CITE-seq
- single-cell multiomics
