This detailed volume provides comprehensive practical guidance on transcriptome data analysis for a variety of scientific purposes. Beginning with general protocols, the collection moves on to explore protocols for gene characterization analysis with RNA-seq data as well as protocols on several new applications of transcriptome studies. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and useful, Transcriptome Data Analysis: Methods and Protocols serves as an ideal guide to the expanding purposes of this field of study.

Next generation sequencing (NGS) has surpassed the traditional Sanger sequencing method to become the main choice for large-scale, genome-wide sequencing studies with ultra-high-throughput production and a huge reduction in costs. The NGS technologies have had enormous impact on the studies of structural and functional genomics in all the life sciences. In this book, Next Generation Sequencing Advances, Applications and Challenges, the sixteen chapters written by experts cover various aspects of NGS including genomics, transcriptomics and methylomics, the sequencing platforms, and the bioinformatics challenges in processing and analysing huge amounts of sequencing data. Following an overview of the evolution of NGS in the brave new world of omics, the book examines the advances and challenges of NGS applications in basic and applied research on microorganisms, agricultural plants and humans. This book is of value to all who are interested in DNA sequencing and bioinformatics across all fields of the life sciences.

Transcriptome analysis is the study of the transcriptome, of the complete set of RNA transcripts that are produced under specific circumstances, using high-throughput methods. Transcription profiling, which follows total changes in the behavior of a cell, is used throughout diverse areas of biomedical research, including diagnosis of disease, biomarker discovery, risk assessment of new drugs or environmental chemicals, etc. Transcriptome analysis is most commonly used to compare specific pairs of samples, for example, tumor tissue versus its healthy counterpart. In this volume, Dr. Pyo Hong discusses the role of long RNA sequences in transcriptome analysis, Dr. Shinichi describes the next-generation single-cell sequencing technology developed by his team, Dr. Prasanta presents transcriptome analysis applied to rice under various environmental factors, Dr. Xiangyuan addresses the reproductive systems of flowering plants and Dr. Sadovsky compares codon usage in conifers.

This volume provides experimental and bioinformatics approaches related to different aspects of gene expression analysis. Divided in three sections chapters detail wet-lab protocols, bioinformatics approaches, single-cell gene expression, highly multiplexed amplicon sequencing, multi-omics techniques, and targeted sequencing. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Gene Expression Analysis: Methods and Protocols aims provide useful information to researchers worldwide.

Transcriptome Profiling: Progress and Prospects assists readers in assessing and interpreting a large number of genes, up to and including an entire genome. It provides key insights into the latest tools and techniques used in transcriptomics and its relevant topics which can reveal a global snapshot of the complete RNA component of a cell at a given time. This snapshot, in turn, enables the distinction between different cell types, different disease states, and different time points during development. Transcriptome analysis has been a key area of biological inquiry for decades. The next-generation sequencing technologies have revolutionized transcriptomics by providing opportunities for multidimensional examinations of cellular transcriptomes in which high-throughput expression data are obtained at a single-base resolution. Transcriptome analysis has evolved from the detection of single RNA molecules to large-scale gene expression profiling and genome annotation initiatives. Written by a team of global experts, key topics in Transcriptome Profiling include transcriptome characterization, expression analysis of transcripts, transcriptome and gene regulation, transcriptome profiling and human health, medicinal plants transcriptomics, transcriptomics and genetic engineering, transcriptomics in agriculture, and phylotranscriptomics. - Presents recent development in the tools and techniques in transcriptomic characterization - Integrates expression analysis of transcripts and gene regulation - Includes the application of transcriptomics in human health, genetic engineering and agriculture

After sequencing the human genome a decade ago, researchers have continued their projects, but now to try to better understand how, and when, genes are expressed in health and disease. Efforts have been concentrated on the measurement of the expression of RNA transcripts. In an analogy to the genome, the term "transcriptome" was created to refer to the complete set of RNAs in a cell type or tissue in a particular situation. Transcriptomics is the science that studies this issue and it is a branch of functional genomics. Transcriptomics in Heath and Disease provides a comprehensive overview of the science of transcriptomics initially in health, focusing on the concept of the transcriptome and the main methods to evaluate it. The authors discuss the concept and use of gene expression signatures and transcriptional biomarkers in normal development and diseased tissues and organs. As the transcriptome changes depending on the pathology, there is also a focus on the variations in the gene expression in different diseases such as autoimmune, inflammation, cancer and infections. This book should be very useful for researchers in molecular biology focusing on gene expression, human genetics, immunology, and genomics.

Contemporary biomedical and clinical research is undergoing constant development thanks to the rapid advancement of various high throughput technologies at the DNA, RNA and protein levels. These technologies can generate vast amounts of raw data, making bioinformatics methodologies essential in their use for basic biomedical and clinical applications. Bioinformatics for biomedical science and clinical applications demonstrates what these cutting-edge technologies can do and examines how to design an appropriate study, including how to deal with data and address specific clinical questions. The first two chapters consider Bioinformatics and analysis of the human genome. The subsequent three chapters cover the introduction of Transcriptomics, Proteomics and Systems biomedical science. The remaining chapters move on to critical developments, clinical information and conclude with domain knowledge and adaptivity.