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Data Analysis for Omic Sciences: Methods and Applications, Volume 82, shows how these types of challenging datasets can be analyzed. Examples of applications in real environmental, clinical and food analysis cases help readers disseminate these approaches. Chapters of note include an Introduction to Data Analysis Relevance in the Omics Era, Omics Experimental Design and Data Acquisition, Microarrays Data, Analysis of High-Throughput RNA Sequencing Data, Analysis of High-Throughput DNA Bisulfite Sequencing Data, Data Quality Assessment in Untargeted LC-MS Metabolomic, Data Normalization and Scaling, Metabolomics Data Preprocessing, and more. - Presents the best reference book for omics data analysis - Provides a review of the latest trends in transcriptomics and metabolomics data analysis tools - Includes examples of applications in research fields, such as environmental, biomedical and food analysis
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.
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.
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.
The large potential of RNA sequencing and other "omics" techniques has contributed to the production of a huge amount of data pursuing to answer many different questions that surround the science's great unknowns. This book presents an overview about powerful and cost-efficient methods for a comprehensive analysis of RNA-Seq data, introducing and revising advanced concepts in data analysis using the most current algorithms. A holistic view about the entire context where transcriptome is inserted is also discussed here encompassing biological areas with remarkable technological advances in the study of systems biology, from microorganisms to precision medicine.
Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.
Widely considered the premier text in pediatric infectious diseases, Feigin and Cherry's Textbook of Pediatric Infectious Diseases, 9th Edition, provides authoritative, up-to-date coverage of this rapidly changing field. Extensively revised by Drs. James Cherry, Sheldon L. Kaplan, Gail J. Demmler-Harrison, William J. Steinbach, Peter J. Hotez, and new editor John V. Williams, this two-volume reference delivers the information you need on epidemiology, public health, preventive medicine, clinical manifestations, diagnosis, treatment, and much more. It serves as a reliable, everyday resource for practicing ID specialists, and an invaluable reference for medical students, residents, and fellows in ID, pediatricians and internists, and others who work with neonates, children, and adolescents or in public health. - Discusses infectious diseases according to organ systems that may be affected, as well as individually by microorganisms, placing emphasis on clinical manifestations that may be related to the organism causing the disease. - Provides detailed information regarding the best means to establish a diagnosis, explicit recommendations for therapy, and the most appropriate uses of diagnostic imaging. - Includes expanded information on Q fever, antibiotic resistance and antibiotic agents, human coronaviruses, pox viruses, and infections in the compromised host, and contains new COVID-19 content across numerous chapters. - Features a new chapter on antimicrobial stewardship, and new coverage of antivirals for pox viruses. - Reflects today's more aggressive infectious and antibiotic-resistant organisms as well as emerging and re-emerging infectious diseases. - Contains hundreds of full-color images (many are new!), including clinical photos, radiographic images, drawings, charts, and graphs. - Enhanced eBook version included with purchase. Your enhanced eBook allows you to access all of the text, figures, and references from the book on a variety of devices. Additional digital ancillary content may publish up to 6 weeks following the publication date. - Any additional digital ancillary content may publish up to 6 weeks following the publication date.
This book brings together what is currently known in terms of basic research in the field of long noncoding RNAs (lncRNAs) and builds on this to delve more deeply in the specific roles that lncRNAs are playing during inflammation. The book provides readers with basic knowledge on lncRNAs: from understanding the complexity of the transcriptome, conservation, structure and the tools used to investigate these aspects, to how we use this information to study lncRNAs in a specific biological context. The volume covers the emerging roles of lncRNAs in the initial stages of inflammation as well as their roles in specific inflammatory diseases including arthritis, lupus, diabetes and cardiovascular disease. The book also shows the emerging interest in using lncRNAs as a therapeutic target and how this could impact our ability to diagnose and treat inflammatory diseases in the future.