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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.
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.
Full four-color book. Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R. All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.
WHOLE GRAINS AND HEALTH The updated guide to whole grains and their integral role in nutritional health In an increasingly health-conscious society, the potential benefits of whole grain products are of paramount importance to manufacturers, dieticians, and consumers alike. Whole Grains and Health covers all aspects of this crucial topic, presenting a data-driven study of whole grains’ functional components, associated biomarkers and overall impact upon human health. Now in its second edition, the text has been revised and expanded to include six new chapters and groundbreaking new data. This essential guide features: Summaries of large research projects on the health effects of whole grain in Europe and the US New data on the associations between whole grain consumption and risk of developing chronic diseases Discussions of metabolomics and their use in addressing health effects and finding new biomarkers of both dietary exposure and health effects related to the diet Information on the use of genomics in studies of how gene-expression profiles change in response to whole grain intake Newly identified bioactive compounds in whole grains and whole grain fractions The new EU regulations on health claims that affect whole grain food products Providing information that will be of interest to food scientists, healthcare specialists and food industry professionals alike, the second edition of Whole Grains and Health is an essential resource for anyone concerned with the impact whole grains may have upon health.
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
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.
Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases
​The recent advances in genomics are continuing to reshape our approach to diagnostics, prognostics and therapeutics in oncologic and other disorders. A paradigm shift in pharmacogenomics and in the diagnosis of genetic inherited diseases and infectious diseases is unfolding as the result of implementation of next generation genomic technologies. With rapidly growing knowledge and applications driving this revolution, along with significant technologic and cost changes, genomic approaches are becoming the primary methods in many laboratories and for many diseases. As a result, a plethora of clinical genomic applications have been implemented in diagnostic pathology laboratories, and the applications and demands continue to evolve rapidly. This has created a tremendous need for a comprehensive resource on genomic applications in clinical and anatomic pathology. We believe that our current textbook provides such a resource to practicing molecular pathologists, hematopathologists and other subspecialized pathologists, general pathologists, pathology and other trainees, oncologists, geneticists and a growing spectrum of other clinicians. With periodic updates and a sufficiently rapid time from submission to publication, this textbook will be the resource of choice for many professionals and teaching programs. Its focus on genomics parallels the evolution of these technologies as primary methods in the clinical lab. The rapid evolution of genomics and its applications in medicine necessitates the (frequent) updating of this publication. This text will provide a state-of-the art review of the scientific principles underlying next generation genomic technologies and the required bioinformatics approaches to analyses of the daunting amount of data generated by current and emerging genomic technologies. Implementation roadmaps for various clinical assays such as single gene, gene panels, whole exome and whole genome assays will be discussed together with issues related to reporting and the pathologist’s role in interpretation and clinical integration of genomic tests results. Genomic applications for site-specific solid tumors and hematologic neoplasms will be detailed. Genomic applications in pharmacogenomics, inherited genetic diseases and infectious diseases will also be discussed. The latest iteration of practice recommendations or guidelines in genomic testing put forth by stakeholder professional organizations such as the College of American Pathology and the Association for Molecular Pathology, will be discussed as well as regulatory issues and laboratory accreditation related to genomic testing. All chapters will be written by experts in their fields and will include the most up to date scientific and clinical information.
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.