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Author: Ion Mandoiu Publisher: John Wiley & Sons ISBN: 1119272165 Category : Computers Languages : en Pages : 464
Book Description
Introduces readers to core algorithmic techniques for next-generation sequencing (NGS) data analysis and discusses a wide range of computational techniques and applications This book provides an in-depth survey of some of the recent developments in NGS and discusses mathematical and computational challenges in various application areas of NGS technologies. The 18 chapters featured in this book have been authored by bioinformatics experts and represent the latest work in leading labs actively contributing to the fast-growing field of NGS. The book is divided into four parts: Part I focuses on computing and experimental infrastructure for NGS analysis, including chapters on cloud computing, modular pipelines for metabolic pathway reconstruction, pooling strategies for massive viral sequencing, and high-fidelity sequencing protocols. Part II concentrates on analysis of DNA sequencing data, covering the classic scaffolding problem, detection of genomic variants, including insertions and deletions, and analysis of DNA methylation sequencing data. Part III is devoted to analysis of RNA-seq data. This part discusses algorithms and compares software tools for transcriptome assembly along with methods for detection of alternative splicing and tools for transcriptome quantification and differential expression analysis. Part IV explores computational tools for NGS applications in microbiomics, including a discussion on error correction of NGS reads from viral populations, methods for viral quasispecies reconstruction, and a survey of state-of-the-art methods and future trends in microbiome analysis. Computational Methods for Next Generation Sequencing Data Analysis: Reviews computational techniques such as new combinatorial optimization methods, data structures, high performance computing, machine learning, and inference algorithms Discusses the mathematical and computational challenges in NGS technologies Covers NGS error correction, de novo genome transcriptome assembly, variant detection from NGS reads, and more This text is a reference for biomedical professionals interested in expanding their knowledge of computational techniques for NGS data analysis. The book is also useful for graduate and post-graduate students in bioinformatics.
Author: Fabio Marchi Publisher: BoD – Books on Demand ISBN: 9535135031 Category : Medical Languages : en Pages : 330
Book Description
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.
Author: Jerzy Kulski Publisher: BoD – Books on Demand ISBN: 9535122401 Category : Medical Languages : en Pages : 466
Book Description
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.
Author: Irina Vlasova-St. Louis Publisher: BoD – Books on Demand ISBN: 1839626860 Category : Science Languages : en Pages : 144
Book Description
This book evaluates and comprehensively summarizes the scientific findings that have been achieved through RNA-sequencing (RNA-Seq) technology. RNA-Seq transcriptome profiling of healthy and diseased tissues allows FOR understanding the alterations in cellular phenotypes through the expression of differentially spliced RNA isoforms. Assessment of gene expression by RNA-Seq provides new insight into host response to pathogens, drugs, allergens, and other environmental triggers. RNA-Seq allows us to accurately capture all subtypes of RNA molecules, in any sequenced organism or single-cell type, under different experimental conditions. Merging genomics and transcriptomic profiling provides novel information underlying causative DNA mutations. Combining RNA-Seq with immunoprecipitation and cross-linking techniques is a clever multi-omics strategy assessing transcriptional, post-transcriptional and post-translational levels of gene expression regulation.
Author: Geraldo A. Passos Publisher: Springer Nature ISBN: 303087821X Category : Science Languages : en Pages : 473
Book Description
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.
Author: Shunfu Mao Publisher: ISBN: Category : Languages : en Pages : 80
Book Description
High throughput sequencing of RNA (RNA-seq) has become a staple in modern molecular biology, with a wide range of applications including RNA transcripts assembly, variants detection, and gene expression estimation for downstream cellular analysis. RNA-seq data is therefore able to provide us with unprecedented insights into cellular organisms. However, they have also introduced a new set of computational challenges because of the nature of the sequenced RNA transcripts and an ever increasing number of RNA-seq experiments. For instance, the RNA transcripts have different expression levels, making the sequenced reads potentially unable to fully cover some lowly expressed gene regions. In addition, the RNA transcripts also share many repetitive patterns, making it ambiguous to determine the regions where some RNA-seq reads are actually sampled. Moreover, there are still many laborious procedures in the RNA-seq data analysis, making it difficult to keep pace with the constantly produced large amounts of RNA-seq data. There is an urgent need for better computational methods that are able to analyze the RNA-seq data more accurately and efficiently. Motivated by this, in the thesis, we have presented novel computational solutions for three computational problems for RNA-seq data analysis: Firstly, we have developed RefShannon - a new genome-guided RNA transcripts (transcriptome) assembly software. RefShannon reconstructs RNA transcripts, based on the alignments of RNA-seq reads onto a reference genome. It exploits the pair-end linking information of RNA-seq reads, and the varying expressions of RNA transcripts, in enabling an accurate reconstruction of the transcripts. Experiments demonstrate RefShannon has superior assembly performance over the state-of-art genome-guided assembly tools. Next, we have developed abSNP - a new RNA-seq SNP calling software. AbSNP detects SNPs in expressed gene regions, based on the alignments of RNA-seq reads onto a reference transcriptome. It exploits the mapping quality scores of RNA-seq reads, and the varying expressions of different genes. AbSNP is a cost-effective method as it requires no additional DNA-seq. It is also able to call SNPs with significantly improved sensitivity in repetitive gene regions, while other RNA-seq SNP callers are unable to make any calls in such regions. Finally, we have developed CellMeSH - a new web server and API package for automatic cell-type identification in single-cell RNA-seq (scRNA-seq) analysis. CellMeSH predicts cell types, based on a set of marker genes as query input. CellMeSH builds its database in a scalable and easy-to-update way using prior literature, and adopts a novel probabilistic method to better query the database. Through a variety of experiments on human and mouse scRNA-seq datasets, CellMeSH has demonstrated richer gene and cell-type information in its database, robust query method, and an overall superior annotation performance.
Author: Publisher: Elsevier ISBN: 0444640452 Category : Science Languages : en Pages : 730
Book Description
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
Author: Susan Carpenter Publisher: Springer Nature ISBN: 3030920348 Category : Science Languages : en Pages : 189
Book Description
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.