Handbook of Translational Transcriptomics: Research, Protocols and Applications provides a comprehensive overview to the field of transcriptomics. With an emphasis on the various protocols and techniques available for investigation, it acts as a practical guide to researchers for implementing their own investigations in the field. The book begins with an overview of the past, present, and potential approaches in the field of transcriptomics, with discussion of choosing the correct approach based on the research needed, it also highlighting the pros and cons of each approach. Following this it explores techniques and protocols for investigating specific approaches focusing on RNA sequencing, expression arrays, and gene expression, providing detailed. It then delves into data analysis and offers recommendations, guidelines, and approaches related to data interpretation. The book also considers the translation of transcriptomics to clinical application and applications in molecular diagnostics, biomarkers in medicine, and personalized medicine specific to oncology, as well as biotechnology for pharmaceutical research. Handbook of Translational Transcriptomics is a detailed reference that provides a complete view of transcriptomics, ranging from methods to handling data and medical applications.

1. Past, current and future of transcriptomics 2. Pitfalls of transcriptomics, and selection of the most appropriate transcriptomic technique 3. RNA sequencing in wet lab 4. Expression arrays in wet lab 5. High-throughput and multiplex PCR in wet lab to measure gene expression 6. Processing primary gene expression data: normalization, harmonization and data QC 7. Data check and comparison with the expression databases 8. Finding differentially expressed genes and gene sets 9. Molecular pathway analysis using transcriptomic data 10. OMICSwise analysis of RNA splicing 11. Transcriptomic biomarkers in medicine 12. Translational transcriptomics for personalized oncology 13. Transcriptomics for modern biotechnology 14. Transcriptomics and quantitative proteomics: competition or symbiosis?