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In RNA Mapping- Methods and Protocols expert researchers in the field detail many of the methods which are now commonly used to study RNA. These include protocols for the consequence of the emerging interest in the characterization of cellular RNAs urged by their potential use as diagnostic biomarkers or therapeutic targets. In particular, the biological relevance of microRNAs in human physiology and disease development is highlighted in the 16 chapters focused on methods for their physical and functional mapping. 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 key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, RNA Mapping- Methods and Protocols provides instruction and inspiration for scientists who are facing the challenges of the discovery and/or functional characterization of RNA molecules for a wide variety of applications ranging from novel biomedical diagnostics to therapeutics and biomaterials.
Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.
With the dramatic increase in RNA 3D structure determination in recent years, we now know that RNA molecules are highly structured. Moreover, knowledge of RNA 3D structures has proven crucial for understanding in atomic detail how they carry out their biological functions. Because of the huge number of potentially important RNA molecules in biology, many more than can be studied experimentally, we need theoretical approaches for predicting 3D structures on the basis of sequences alone. This volume provides a comprehensive overview of current progress in the field by leading practitioners employing a variety of methods to model RNA 3D structures by homology, by fragment assembly, and by de novo energy and knowledge-based approaches.
This first book on the market covers the many new and important RNA species discovered over the past five years, explaining current methods for the enrichment, separation and purification of these novel RNAs. Building up from general principles of RNA biochemistry and biophysics, this book addresses the practical aspects relevant to the laboratory researcher throughout, while discussing the performance and potential problems of the methods discussed. An appendix contains a glossary with the important terms and techniques used in RNA analysis. By explaining the basic and working principles of the methods, the book allows biochemists and molecular biologists to gain much more expertise than by simply repeating a pre-formulated protocol, enabling them to select the procedure and materials best suited to the RNA analysis task at hand. As a result, they will be able to develop new protocols where needed and optimize and fine-tune the general purpose standard protocols that come with the purification equipment and instrumentation.
The State of the Art in Transcriptome AnalysisRNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical Approach enables researchers to examine differential expression at gene, exon, and transcript le
Specific complexes of protein and RNA carry out many essential biological functions, including RNA processing, RNA turnover, RNA folding, as well as the translation of genetic information from mRNA into protein sequences. Messenger RNA (mRNA) decay is now emerging as an important control point and a major contributor to gene expression. Continuing identification of the protein factors and cofactors, and mRNA instability elements responsible for mRNA decay allow researchers to build a comprehensive picture of the highly orchestrated processes involved in mRNA decay and its regulation. Covers the nonsense-mediated mRNA decay (NMD) or mRNA surveillance pathway Expert researchers introduce the most advanced technologies and techniques to identify mRNA processing, transport, localization and turnover, which are central to the process of gene expression Offers step-by-step lab instructions, including necessary equipment and reagents
In RNA Mapping- Methods and Protocols expert researchers in the field detail many of the methods which are now commonly used to study RNA. These include protocols for the consequence of the emerging interest in the characterization of cellular RNAs urged by their potential use as diagnostic biomarkers or therapeutic targets. In particular, the biological relevance of microRNAs in human physiology and disease development is highlighted in the 16 chapters focused on methods for their physical and functional mapping. 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 key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, RNA Mapping- Methods and Protocols provides instruction and inspiration for scientists who are facing the challenges of the discovery and/or functional characterization of RNA molecules for a wide variety of applications ranging from novel biomedical diagnostics to therapeutics and biomaterials.