Full Description
The study of transcriptomics is key to understanding complex diseases. This new edition will build on the foundation of the first edition while incorporating the progress that has been made in the field of transcriptomics in the past six years, including bioinformatics for data analysis. Written by leading experts, chapters address new subjects such as methodological advances in large-scale sequencing, the sequencing of single-cells, and spatial transcriptomics. The new edition will address how transcriptomics may be used in combination with genetic strategies to identify causative genes in monogenic and complex genetic diseases. Coverage will also explore transcriptomics in challenging groups of diseases, such as cancer, inflammation, bacterial infection, and autoimmune diseases. The updated volume will be useful for geneticists, genome biologists, biomedical researchers, molecular biologists, bioinformaticians, and students, among others.
Contents
1. What is the transcriptome and how it is evaluated?.- 2. ALTERNATIVE SPLICING OF PRE-MESSENGER RNA.- 3. Transcriptome Analysis Using RNA-seq and scRNA-seq.- 4. TRANSCRIPTOMICS OF NEONATAL AND INFANT HUMAN THYMUS.- 5. Transcriptomics at the single cell level and human diseases: opportunities and challenges in data processing and analysis.- 6. METHODS FOR GENE CO-EXPRESSION NETWORK VISUALIZATION AND ANALYSIS.- 7. Comparative Analysis of Packages and Algorithms for the Analysis of Spatially Resolved Transcriptomics Data.- 8. The Interplay Between the Transcriptomics and Proteomics Profiles.- 9. TRANSCRIPTOME DURING NORMAL CELL DIFFERENTIATION.- 10. Transcriptomics to dissect the Immune System.- 11. Transcriptome Profiling in Autoimmune Diseases.- 12. Transcriptome Profiling in Experimental Inflammatory Arthritis.- 13. TRANSCRIPTOMICS AND IMMUNE RESPONSE IN HUMAN CANCER.- 14. MicroRNAs in Cancer.- 15. OxidativeStress, DNA Damage and Transcriptional Expression of DNA Repair and Stress Response Genes in Diabetes Mellitus.- 16. Large-scale gene expression in monogenic and complex genetic diseases.- 17. Transcriptome in Human Mycoses.- 18. Understanding Chagas Disease by Multi-omics data Integration, Functional and Enrichment Computational Analysis.
