Integrative Multi-Omics in Biomedical Research PDF Download

Author:
Publisher:
ISBN: 9783036525822
Category : Science
Languages : en
Pages : 178

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Author: Preeti Arivaradarajan
Publisher: Springer
ISBN: 9811329257
Category : Science
Languages : en
Pages : 158

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Book Description
This book is a concerted effort to put together the rapidly growing facets of biological data. It provides a platform for the readers to think about integrative approaches to solve complex biological problems. This fundamental book deals with the simplest concepts of omics to recent advancements in the field. The content is divided into seven chapters that provide insight into various omics approaches, omics technologies, and its applications. Each chapter delves into different molecular scales: genomics, transcriptomics, proteomics, and metabolomics. Further to provide a holistic view a chapter detailing microbiome has been included in the book. The sub-sections in the chapters is dedicated to introducing the various analytical tools such as next generation sequencing, chromatin immunoprecipitation, mass spectrometry, peptide mass fingerprinting, RNA Seq and NMR spectroscopy. It entails a chapter focused on the bioinformatics resources for analysis of the omics data. In summary, this comprehensive book emphasizes the recent advancements in the study of biomolecules spanning from DNA to metabolites.

Author: Manish Kumar Gupta
Publisher: Elsevier
ISBN: 0443160937
Category : Science
Languages : en
Pages : 434

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Book Description
Integrative Omics: Concepts, Methodology and Applications provides a holistic and integrated view of defining and applying network approaches, integrative tools, and methods to solve problems for the rationalization of genotype to phenotype relationships. The reference includes a range of chapters in a systemic 'step by step' manner, which begins with the basic concepts from Omic to Multi Integrative Omics approaches, followed by their full range of approaches, applications, emerging trends, and future trends. All key areas of Omics are covered including biological databases, sequence alignment, pharmacogenomics, nutrigenomics and microbial omics, integrated omics for Food Science and Identification of genes associated with disease, clinical data integration and data warehousing, translational omics as well as omics technology policy and society research. Integrative Omics: Concepts, Methodology and Applications highlights the recent concepts, methodologies, advancements in technologies and is also well-suited for researchers from both academic and industry background, undergraduate and graduate students who are mainly working in the area of computational systems biology, integrative omics and translational science. The book bridges the gap between biological sciences, physical sciences, computer science, statistics, data science, information technology and mathematics by presenting content specifically dedicated to mathematical models of biological systems. - Provides a holistic, integrated view of a defining and applying network approach, integrative tools, and methods to solve problems for rationalization of genotype to phenotype relationships - Offers an interdisciplinary approach to Databases, data analytics techniques, biological tools, network construction, analysis, modeling, prediction and simulation of biological systems leading to 'translational research', i.e., drug discovery, drug target prediction, and precision medicine - Covers worldwide methods, concepts, databases, and tools used in the construction of integrated pathways

Author: George Tseng
Publisher: Cambridge University Press
ISBN: 1107069114
Category : Mathematics
Languages : en
Pages : 497

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Book Description
Tutorial chapters by leaders in the field introduce state-of-the-art methods to handle information integration problems of omics data.

Author: Saif Hameed
Publisher:
ISBN: 9789811606922
Category :
Languages : en
Pages : 0

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Book Description
This book examines applications of multi-omics approaches for understanding disease etiology, pathogenesis, host-pathogen interactions. It also analyzes the genetics, immunological and metabolic mechanisms underlying the infections. The book also explores genomics, transcriptomics, translational-omics, and metabolomics approaches to understand the pathogenesis and identify potential drug targets. It reviews the role of epigenetic reprogramming in shaping the host-pathogen interactions and presents bioinformatics application in the identification of drug targets. Further, it examines the potential applications of RNA sequencing and non-coding RNA profiling to identify the pathogenesis. Lastly, it offers the current challenges, technological advances, and prospects of using multi-omics technologies in infectious biology.

Author: Joanne Trinh
Publisher: Elsevier
ISBN: 0443135517
Category : Medical
Languages : en
Pages : 276

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Book Description
Integrative Omics in Parkinson's Disease provides a comprehensive understanding of the current literature on high-throughput technologies relating to discoveries for Parkinson's disease etiology. This emerging field uses large omics datasets to investigate the etiology of Parkinson's disease and other forms of parkinsonism. The book traces the evolution of omics technologies from the discovery of monogenic Parkinson's disease forms. Chapters delve into genomics, transcriptomics, epigenomics, artificial intelligence, and gene-environment interactions. Furthermore, it examines the potential therapeutic applications of these advancements and provides insights into the future of omics research in Parkinson's disease. - Reviews evolution of omics technologies from the first identification of monogenic forms of Parkinson's disease - Outlines machine learning algorithm application to Parkinson's disease datasets - Reviews big datasets on gene-environment interactions, genomics, epigenetics, and transcriptomics - Identifies how the microbiome influences Parkinson's disease in mouse models and patients - Provides outlook for therapies with induced-pluripotent stem cell models

Author: Momiao Xiong
Publisher: CRC Press
ISBN: 135117262X
Category : Mathematics
Languages : en
Pages : 580

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Book Description
Big Data in Omics and Imaging: Integrated Analysis and Causal Inference addresses the recent development of integrated genomic, epigenomic and imaging data analysis and causal inference in big data era. Despite significant progress in dissecting the genetic architecture of complex diseases by genome-wide association studies (GWAS), genome-wide expression studies (GWES), and epigenome-wide association studies (EWAS), the overall contribution of the new identified genetic variants is small and a large fraction of genetic variants is still hidden. Understanding the etiology and causal chain of mechanism underlying complex diseases remains elusive. It is time to bring big data, machine learning and causal revolution to developing a new generation of genetic analysis for shifting the current paradigm of genetic analysis from shallow association analysis to deep causal inference and from genetic analysis alone to integrated omics and imaging data analysis for unraveling the mechanism of complex diseases. FEATURES Provides a natural extension and companion volume to Big Data in Omic and Imaging: Association Analysis, but can be read independently. Introduce causal inference theory to genomic, epigenomic and imaging data analysis Develop novel statistics for genome-wide causation studies and epigenome-wide causation studies. Bridge the gap between the traditional association analysis and modern causation analysis Use combinatorial optimization methods and various causal models as a general framework for inferring multilevel omic and image causal networks Present statistical methods and computational algorithms for searching causal paths from genetic variant to disease Develop causal machine learning methods integrating causal inference and machine learning Develop statistics for testing significant difference in directed edge, path, and graphs, and for assessing causal relationships between two networks The book is designed for graduate students and researchers in genomics, epigenomics, medical image, bioinformatics, and data science. Topics covered are: mathematical formulation of causal inference, information geometry for causal inference, topology group and Haar measure, additive noise models, distance correlation, multivariate causal inference and causal networks, dynamic causal networks, multivariate and functional structural equation models, mixed structural equation models, causal inference with confounders, integer programming, deep learning and differential equations for wearable computing, genetic analysis of function-valued traits, RNA-seq data analysis, causal networks for genetic methylation analysis, gene expression and methylation deconvolution, cell –specific causal networks, deep learning for image segmentation and image analysis, imaging and genomic data analysis, integrated multilevel causal genomic, epigenomic and imaging data analysis.

Author: Shailza Singh
Publisher: Springer
ISBN: 9811086931
Category : Medical
Languages : en
Pages : 261

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Book Description
The book uses an integrated approach to predict the behavior of various biological interactions. It further discusses how synthetic biology gathers the information about various systems, in order to either devise an entirely new system, or, to modulate existing systems. The book also tackles the concept of modularity, where biological systems are visualized in terms of their parts. The chapters discuss how the principles of engineering are being used in biomedical sciences, to design biological circuits that can harbor multiple inputs and generate multiple outputs; to create genetic networks and control gene activity, in order to generate a desired response. The book aims to help the readers develop an array of biological parts, and to use these parts to develop synthetic circuits that can be assembled like electronic circuits. The ultimate aim of the book will be to serve as an amalgamation of key ideas of how judiciously synthetic biology could be exploited in therapeutic device and delivery mechanism.

Author: Saif Hameed
Publisher: Springer Nature
ISBN: 9811606919
Category : Medical
Languages : en
Pages : 538

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Book Description
This book examines applications of multi-omics approaches for understanding disease etiology, pathogenesis, host-pathogen interactions. It also analyzes the genetics, immunological and metabolic mechanisms underlying the infections. The book also explores genomics, transcriptomics, translational-omics, and metabolomics approaches to understand the pathogenesis and identify potential drug targets. It reviews the role of epigenetic reprogramming in shaping the host-pathogen interactions and presents bioinformatics application in the identification of drug targets. Further, it examines the potential applications of RNA sequencing and non-coding RNA profiling to identify the pathogenesis. Lastly, it offers the current challenges, technological advances, and prospects of using multi-omics technologies in infectious biology.

Author: Debmalya Barh
Publisher: CRC Press
ISBN: 1439850097
Category : Medical
Languages : en
Pages : 609

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Book Description
A reflection of the explosion of research and development in this field, OMICS: Biomedical Perspectives and Applications explores applications of omics in bioinformatics, cancer research and therapy, diabetes research, plant science, molecular biology, and neurosciences. A select editorial panel of experts discusses their cutting edge omics researc