Buch, Englisch, 390 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Population Genomics
From Cell to Shell
Buch, Englisch, 390 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Population Genomics
ISBN: 978-3-030-40950-0
Verlag: Springer
Single-cell genomics, transcriptomics and epigenomics research is providing new insights into inter-cellular population genomic diversity, heterogeneity, specialization, taxonomy, spatial and temporal gene regulation, and cellular and organismal development and evolution. It is facilitating plant breeding, understanding of human disease conditions and personalized medicine. This book discusses the perspectives, progress, and promises of single-cell genomics, transcriptomics and epigenomics research and applications in addressing the above and other key biological aspects in all organisms. It establishes the current state-of-the-field and serves as the foundation for future developments in single-cell genomics, transcriptomics, and epigenomics.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Naturwissenschaften Biowissenschaften Biowissenschaften Genetik und Genomik (nichtmedizinisch)
- Naturwissenschaften Biowissenschaften Botanik Pflanzenreproduktion, Verbreitung, Genetik
- Naturwissenschaften Biowissenschaften Biowissenschaften Evolutionsbiologie
- Naturwissenschaften Biowissenschaften Tierkunde / Zoologie Tiergenetik, Reproduktion
- Geowissenschaften Umweltwissenschaften Biodiversität
Weitere Infos & Material
Preface.- Single-Cell Genomics, Transcriptomics and Epigenomics: Current State and Future Perspectives.- Single-cell genomics.- Single-cell transcriptomics.- Single-cell epigenomics.- Single-cell metagenomics.- Single-cell Hi-C.- Single-cell ATAC-Seq.- Practical considerations for designing single-cell experiments.- Visualization of single-cell genomic, transcriptomic and epigenomic data.- Addressing the problem of large single-cell genomic, transcriptomic and epigenomic data.- Data analysis tools and statistical methods.- Role of Artificial Intelligence (AI) and deep learning.- Overview of clustering methods and batch effects in single-cell RNA Sequencing.- Best practices for single-cell RNA-Seq data analysis.- Advanced disease modeling.- Tracking mutations, copy number variations, and chromosomal aberrations at the single-cell level.- Defining cell types and states from single-cell genomics.- Unravelling single cell heterogeneity using single-cell RNA sequencing and understanding function of cellular specialization.- Building a taxonomy of the cells.- Characterization of the epigenetic landscape of cellular populations.- Microbial population genetics using single-cell genomics.- Spatial and temporal gene regulation dynamics at the single-cell level.- Single-cell spatial and temporal gene expression patterns in mice.- Single-cell spatial and temporal gene expression patterns in humans.- New insights into cellular development and evolution from single-cell genomics.- Assessing embryo development and regeneration via single-cell RNA-Seq.- Reconstructing lineages from single-cell genomics.- Understanding human diseases using single-cell omics approaches.- Single-cell omics for personalized medicine.- Advanced understanding of cancer using single-cell transcriptomics.- Dissecting Alzheimer's disease at the single-cell level.- Single-cell mass cytometry of differential immune and drug responses.- Challenges and opportunities of single-cell genomics, transcriptomicsand epigenomics in plants.- Systems biology of plants at the single-cell level.- Single-cell genomics for new and enhanced green revolution.- Single-cell genome, transcriptome and epigenome sequencing.- Integration and harmonization of single-cell genomic, transcriptomic and epigenomic data.- Integration of single cell RNA-Seq with CRISPR/Cas9.- Index.