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    Single-Cell Omics

    Single-Cell Omics

    - Volume 1: Technological Advances and Applications

    Forfatter: info mangler
    Bog
    • Format
    • Bog, paperback
    • Engelsk

    Beskrivelse

    Single-Cell Omics: Volume 1: Technological Advances and Applications provides the latest technological developments and applications of single-cell technologies in the field of biomedicine. In the current era of precision medicine, the single-cell omics technology is highly promising due to its potential in diagnosis, prognosis and therapeutics. Sections in the book cover single-cell omics research and applications, diverse technologies applied in the topic, such as pangenomics, metabolomics, and multi-omics of single cells, data analysis, and several applications of single-cell omics within the biomedical field, for example in cancer, metabolic and neuro diseases, immunology, pharmacogenomics, personalized medicine and reproductive health. This book is a valuable source for bioinformaticians, molecular diagnostic researchers, clinicians and members of the biomedical field who are interested in understanding more about single-cell omics and its potential for research and diagnosis.

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    Detaljer
    • SprogEngelsk
    • Sidetal490
    • Udgivelsesdato07-06-2019
    • ISBN139780128149195
    • Forlag Academic Press Inc
    • FormatPaperback
    Størrelse og vægt
  • Vægt970 g
    • coffee cup img
    10 cm
    book img
    19,1 cm
    23,5 cm

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    Cancer Gene expression. Genomics Immunology Mass spectrometry Analysis Cell death Processing Microfluidics Proteins Metabolites Workflow Biomechanics Morphology Nucleases Visualization Bioinformatics Proteomics Mosaicism Systems Biology Metagenomics Epigenomics Transcriptome -omics Cas9 Biorobotics FACS Budding yeast Long noncoding RNA INTACT Challenges LncRNA Noncoding RNA Single cell analysis Sequencing Omics Clustering Applications Technologies Stem-cell biology Single-cell Lab-on--a-chip Cancer biology Cellular heterogeneity Mass spectrometry imaging Raman Cell Growth Transcriptomics Cancer Cell Biology Embryogenesis Tumor heterogeneity Cell isolation Phylogenetics Tumor progression Single-cell RNA-sequencing Imputation Cellular functions MiRNA Single-cell genomics CRISPR Targeted therapy SERS 'omics technologies Macs Mass cytometry Tumor evolution Cell heterogeneity BITS-ChIP Bulk sample sequencing Coding RNA Fluorescence flow cytometry High-content imaging hiPSCs Label-free analysis Laser-capture microdissection LMD/LCM lincRNA miRAP Noninvasive analysis Muscle metabolism Nu-TRAP Pseudotime trajectory construction Phenotypic potential Ribo-Tag/TRAP Single-cell proteomics (SCP) Single muscle fiber Intratumor heterogeneity Myofiber Poly(A) mRNA tagging Single-cell metabolomics Single-cell omics Targeted DamID (TaDa) Single-cell isolation Single-cell multiomics Single-cell computational analysis Stochastic gene expression whole genome
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