Integrative Omics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Integrative Omics write by Manish Kumar Gupta. This book was released on 2024-05-10. Integrative Omics available in PDF, EPUB and Kindle. 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
Integrative Multi-Omics in Biomedical Research
Integrative Multi-Omics in Biomedical Research - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Integrative Multi-Omics in Biomedical Research write by . This book was released on 2021-12-13. Integrative Multi-Omics in Biomedical Research available in PDF, EPUB and Kindle.
Omics Approaches, Technologies And Applications
Omics Approaches, Technologies And Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Omics Approaches, Technologies And Applications write by Preeti Arivaradarajan. This book was released on 2019-02-04. Omics Approaches, Technologies And Applications available in PDF, EPUB and Kindle. 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.
Integrated Omics Approaches to Infectious Diseases
Integrated Omics Approaches to Infectious Diseases - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Integrated Omics Approaches to Infectious Diseases write by Saif Hameed. This book was released on 2021. Integrated Omics Approaches to Infectious Diseases available in PDF, EPUB and Kindle. 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.
Big Data in Omics and Imaging
Big Data in Omics and Imaging - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Big Data in Omics and Imaging write by Momiao Xiong. This book was released on 2018-06-14. Big Data in Omics and Imaging available in PDF, EPUB and Kindle. 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.
