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Author: Joao Carlos Setubal
Publisher: Frontiers Media SA
ISBN: 2889664376
Category : Science
Languages : en
Pages : 170
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Book Description
Author: Joao Carlos Setubal
Publisher: Frontiers Media SA
ISBN: 2889664376
Category : Science
Languages : en
Pages : 170
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Book Description
Author: Setubal
Publisher: Frontiers Media SA
ISBN: 2832506402
Category : Science
Languages : en
Pages : 223
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Book Description
Author: Himel Mallick
Publisher: Frontiers Media SA
ISBN: 2889660915
Category : Science
Languages : en
Pages : 170
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Book Description
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Author: David J. Balding
Publisher: John Wiley & Sons
ISBN: 1119429250
Category : Science
Languages : en
Pages : 1828
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Book Description
A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.
Author: Robert G. Beiko
Publisher:
ISBN: 9781493987283
Category : Microbiology
Languages : en
Pages : 324
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Book Description
Author: Ion Mandoiu
Publisher: John Wiley & Sons
ISBN: 1118169484
Category : Computers
Languages : en
Pages : 460
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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: Somnath Datta
Publisher: Springer Nature
ISBN: 3030733513
Category : Medical
Languages : en
Pages : 349
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Book Description
Microbiome research has focused on microorganisms that live within the human body and their effects on health. During the last few years, the quantification of microbiome composition in different environments has been facilitated by the advent of high throughput sequencing technologies. The statistical challenges include computational difficulties due to the high volume of data; normalization and quantification of metabolic abundances, relative taxa and bacterial genes; high-dimensionality; multivariate analysis; the inherently compositional nature of the data; and the proper utilization of complementary phylogenetic information. This has resulted in an explosion of statistical approaches aimed at tackling the unique opportunities and challenges presented by microbiome data. This book provides a comprehensive overview of the state of the art in statistical and informatics technologies for microbiome research. In addition to reviewing demonstrably successful cutting-edge methods, particular emphasis is placed on examples in R that rely on available statistical packages for microbiome data. With its wide-ranging approach, the book benefits not only trained statisticians in academia and industry involved in microbiome research, but also other scientists working in microbiomics and in related fields.
Author: Wontack Han
Publisher:
ISBN:
Category : Bioinformatics
Languages : en
Pages : 0
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Book Description
Microbial organisms play key roles in the human hosts' health and diseases. Recent advancements in genome sequencing have resulted in a large collection of sequencing data of microbial species and have expanded the research of microbiome from the characterization of microbiomes' community associated with different environments/hosts to the applications related with human health and diseases. Computational methods have been developed to identify microbial markers from microbiome datasets derived from cohorts of patients with different diseases. Predictive models based on these markers (features) have been built for discriminating host phenotypes such as disease vs healthy and cancer immunotherapy responder vs non-responder. In this dissertation, I developed computational methods for comparative analysis of metagenomes from raw sequencing data and developed Machine Learning (ML) approaches to build predictive models for host phenotype prediction based on identified microbial markers. First, I implemented the subtractive assembly method(called CoSA) for comparative metagenomics that directly detects differential reads between two groups of metagenomes, from which microbial marker genes could be assembled and characterized. Secondly, I reported the curation of a repository of microbial marker genes and predictive models built from these markers for microbiome-based prediction of host phenotype, and a computational pipeline(named Mi2P) for using the repository. Lastly, I exploited locality sensitive hashing(LSH) as clustering algorithm to group billions of k-mers having similar abundance profiles across multiple samples into k-mers co-abundance groups (kCAGs) to improve the characterization of differential microbial markers. The overall goal of my research is to develop fast and efficient approaches for identifying microbial marker genes, and make them available for building predictive models for microbiome-based host phenotype predictions.
Author: Robert G. Beiko
Publisher: Humana
ISBN: 9781493993765
Category : Science
Languages : en
Pages : 324
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Book Description
This volume aims to capture the entire microbiome analysis pipeline, sample collection, quality assurance, and computational analysis of the resulting data. Chapters detail several example applications of microbiome research, and the protocols described in this book are complemented with short perspectives about the history, current state, and future directions of protocols in microbiomics. 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, Microbiome Analysis: Methods and Protocols aims to ensure successful results in the further study of this vital field.
Author: Jacques Izard
Publisher: Academic Press
ISBN: 0124105084
Category : Science
Languages : en
Pages : 188
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Book Description
Concisely discussing the application of high throughput analysis to move forward our understanding of microbial principles, Metagenomics for Microbiology provides a solid base for the design and analysis of omics studies for the characterization of microbial consortia. The intended audience includes clinical and environmental microbiologists, molecular biologists, infectious disease experts, statisticians, biostatisticians, and public health scientists. This book focuses on the technological underpinnings of metagenomic approaches and their conceptual and practical applications. With the next-generation genomic sequencing revolution increasingly permitting researchers to decipher the coding information of the microbes living with us, we now have a unique capacity to compare multiple sites within individuals and at higher resolution and greater throughput than hitherto possible. The recent articulation of this paradigm points to unique possibilities for investigation of our dynamic relationship with these cellular communities, and excitingly the probing of their therapeutic potential in disease prevention or treatment of the future. Expertly describes the latest metagenomic methodologies and best-practices, from sample collection to data analysis for taxonomic, whole shotgun metagenomic, and metatranscriptomic studies Includes clear-headed pointers and quick starts to direct research efforts and increase study efficacy, eschewing ponderous prose Presented topics include sample collection and preparation, data generation and quality control, third generation sequencing, advances in computational analyses of shotgun metagenomic sequence data, taxonomic profiling of shotgun data, hypothesis testing, and mathematical and computational analysis of longitudinal data and time series. Past-examples and prospects are provided to contextualize the applications.
