Computational and Statistical Epigenomics

Computational and Statistical Epigenomics PDF Author: Andrew E. Teschendorff
Publisher: Springer
ISBN: 940179927X
Category : Science
Languages : en
Pages : 218

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Book Description
This book introduces the reader to modern computational and statistical tools for translational epigenomics research. Over the last decade, epigenomics has emerged as a key area of molecular biology, epidemiology and genome medicine. Epigenomics not only offers us a deeper understanding of fundamental cellular biology, but also provides us with the basis for an improved understanding and management of complex diseases. From novel biomarkers for risk prediction, early detection, diagnosis and prognosis of common diseases, to novel therapeutic strategies, epigenomics is set to play a key role in the personalized medicine of the future. In this book we introduce the reader to some of the most important computational and statistical methods for analyzing epigenomic data, with a special focus on DNA methylation. Topics include normalization, correction for cellular heterogeneity, batch effects, clustering, supervised analysis and integrative methods for systems epigenomics. This book will be of interest to students and researchers in bioinformatics, biostatistics, biologists and clinicians alike. Dr. Andrew E. Teschendorff is Head of the Computational Systems Genomics Lab at the CAS-MPG Partner Institute for Computational Biology, Shanghai, China, as well as an Honorary Research Fellow at the UCL Cancer Institute, University College London, UK.

Computational and Statistical Epigenomics

Computational and Statistical Epigenomics PDF Author: Andrew E. Teschendorff
Publisher: Springer
ISBN: 940179927X
Category : Science
Languages : en
Pages : 218

Get Book Here

Book Description
This book introduces the reader to modern computational and statistical tools for translational epigenomics research. Over the last decade, epigenomics has emerged as a key area of molecular biology, epidemiology and genome medicine. Epigenomics not only offers us a deeper understanding of fundamental cellular biology, but also provides us with the basis for an improved understanding and management of complex diseases. From novel biomarkers for risk prediction, early detection, diagnosis and prognosis of common diseases, to novel therapeutic strategies, epigenomics is set to play a key role in the personalized medicine of the future. In this book we introduce the reader to some of the most important computational and statistical methods for analyzing epigenomic data, with a special focus on DNA methylation. Topics include normalization, correction for cellular heterogeneity, batch effects, clustering, supervised analysis and integrative methods for systems epigenomics. This book will be of interest to students and researchers in bioinformatics, biostatistics, biologists and clinicians alike. Dr. Andrew E. Teschendorff is Head of the Computational Systems Genomics Lab at the CAS-MPG Partner Institute for Computational Biology, Shanghai, China, as well as an Honorary Research Fellow at the UCL Cancer Institute, University College London, UK.

Computational Epigenetics and Diseases

Computational Epigenetics and Diseases PDF Author:
Publisher: Academic Press
ISBN: 0128145145
Category : Medical
Languages : en
Pages : 452

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Book Description
Computational Epigenetics and Diseases, written by leading scientists in this evolving field, provides a comprehensive and cutting-edge knowledge of computational epigenetics in human diseases. In particular, the major computational tools, databases, and strategies for computational epigenetics analysis, for example, DNA methylation, histone modifications, microRNA, noncoding RNA, and ceRNA, are summarized, in the context of human diseases. This book discusses bioinformatics methods for epigenetic analysis specifically applied to human conditions such as aging, atherosclerosis, diabetes mellitus, schizophrenia, bipolar disorder, Alzheimer disease, Parkinson disease, liver and autoimmune disorders, and reproductive and respiratory diseases. Additionally, different organ cancers, such as breast, lung, and colon, are discussed. This book is a valuable source for graduate students and researchers in genetics and bioinformatics, and several biomedical field members interested in applying computational epigenetics in their research. - Provides a comprehensive and cutting-edge knowledge of computational epigenetics in human diseases - Summarizes the major computational tools, databases, and strategies for computational epigenetics analysis, such as DNA methylation, histone modifications, microRNA, noncoding RNA, and ceRNA - Covers the major milestones and future directions of computational epigenetics in various kinds of human diseases such as aging, atherosclerosis, diabetes, heart disease, neurological disorders, cancers, blood disorders, liver diseases, reproductive diseases, respiratory diseases, autoimmune diseases, human imprinting disorders, and infectious diseases

Epigenetics Methods

Epigenetics Methods PDF Author: Trygve O Tollefsbol
Publisher: Academic Press
ISBN: 0128194154
Category : Medical
Languages : en
Pages : 740

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Book Description
In recent years, the field of epigenetics has grown significantly, driving new understanding of human developmental processes and disease expression, as well as advances in diagnostics and therapeutics. As the field of epigenetics continues to grow, methods and technologies have multiplied, resulting in a wide range of approaches and tools researchers might employ. Epigenetics Methods offers comprehensive instruction in methods, protocols, and experimental approaches applied in field of epigenetics. Here, across thirty-five chapters, specialists offer step-by-step overviews of methods used to study various epigenetic mechanisms, as employed in basic and translational research. Leading the reader from fundamental to more advanced methods, the book begins with thorough instruction in DNA methylation techniques and gene or locus-specific methylation analyses, followed by histone modification methods, chromatin evaluation, enzyme analyses of histone methylation, and studies of non-coding RNAs as epigenetic modulators. Recently developed techniques and technologies discussed include single-cell epigenomics, epigenetic editing, computational epigenetics, systems biology epigenetic methods, and forensic epigenetic approaches. Epigenetics methods currently in-development, and their implication for future research, are also considered in-depth. In addition, as with the wider life sciences, reproducibility across experiments, labs, and subdisciplines is a growing issue for epigenetics researchers. This volume provides consensus-driven methods instruction and overviews. Tollefsbol and contributing authors survey the range of existing methods; identify best practices, common themes, and challenges; and bring unity of approach to a diverse and ever-evolving field. - Includes contributions by leading international investigators involved in epigenetic research and clinical and therapeutic application - Integrates technology and translation with fundamental chapters on epigenetics methods, as well as chapters on more novel and advanced epigenetics methods - Written at verbal and technical levels that can be understood by scientists and students alike - Includes chapters on state-of-the-art techniques such as single-cell epigenomics, use of CRISPR/Cas9 for epigenetic editing, and epigenetics methods applied to forensics

Epigenetic Biomarkers and Diagnostics

Epigenetic Biomarkers and Diagnostics PDF Author: Jose Luis Garcia-Gimenez
Publisher: Academic Press
ISBN: 0128019212
Category : Science
Languages : en
Pages : 698

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Book Description
Epigenetic Biomarkers and Diagnostics comprises 31 chapters contributed by leading active researchers in basic and clinical epigenetics. The book begins with the basis of epigenetic mechanisms and descriptions of epigenetic biomarkers that can be used in clinical diagnostics and prognostics. It goes on to discuss classical methods and next generation sequencing-based technologies to discover and analyze epigenetic biomarkers. The book concludes with an account of DNA methylation, post-translational modifications and noncoding RNAs as the most promising biomarkers for cancer (i.e. breast, lung, colon, etc.), metabolic disorders (i.e. diabetes and obesity), autoimmune diseases, infertility, allergy, infectious diseases, and neurological disorders. The book describes the challenging aspects of research in epigenetics, and current findings regarding new epigenetic elements and modifiers, providing guidance for researchers interested in the most advanced technologies and tested biomarkers to be used in the clinical diagnosis or prognosis of disease. - Focuses on recent progress in several areas of epigenetics, general concepts regarding epigenetics, and the future prospects of this discipline in clinical diagnostics and prognostics - Describes the importance of the quality of samples and clinical associated data, and also the ethical issues for epigenetic diagnostics - Discusses the advances in epigenomics technologies, including next-generation sequencing based tools and applications - Expounds on the utility of epigenetic biomarkers for diagnosis and prognosis of several diseases, highlighting the study of these biomarkers in cancer, cardiovascular and metabolic diseases, infertility, and infectious diseases - Includes a special section that discusses the relevance of biobanks in the maintenance of high quality biosamples and clinical-associated data, and the relevance of the ethical aspects in epigenetic studies

Bioinformatics: Sequences, Structures, Phylogeny

Bioinformatics: Sequences, Structures, Phylogeny PDF Author: Asheesh Shanker
Publisher: Springer
ISBN: 9811315620
Category : Science
Languages : en
Pages : 402

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Book Description
This book provides a comprehensive overview of the concepts and approaches used for sequence, structure, and phylogenetic analysis. Starting with an introduction to the subject and intellectual property protection for bioinformatics, it guides readers through the latest sequencing technologies, sequence analysis, genomic variations, metagenomics, epigenomics, molecular evolution and phylogenetics, structural bioinformatics, protein folding, structure analysis and validation, drug discovery, reverse vaccinology, machine learning, application of R programming in biological data analysis, and the use of Linux in handling large data files.

Epigenomics

Epigenomics PDF Author: Gurbachan Singh Miglani
Publisher: I K International Pvt Ltd
ISBN: 9390620724
Category : Medical
Languages : en
Pages : 710

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Book Description
Epigenomics deals in detail with the concepts, principles, procedures, developments, limitations, advantages, applications and future prospects of different areas of epigenomics in a comprehensive manner. It provides concise yet complete knowledge on the many aspects of the basic and most recent methods and applications in epigenomics, a branch of epigenetics that deals with the mechanisms such as DNA modifications, histone modifications, RNA modifications, small and long non-coding RNAs, chromatin remodeling, which are involved in epigenetic control of gene expression without involving variations in DNA sequences. These regulatory mechanisms lead to phenotypic variations. These epigenetic mechanisms can be exploited for crop improvement and cure of human diseases. Epigenomics strives to understand the role of epigenetic marks (chemical tags) in the development of phenotype. This understanding provides epigeneticists to apply epigenomics in medicine and agriculture. Self-explanatory adequately labelled figures have been the special emphasis throughout. This book is primarily designed for senior undergraduate and graduate level (M.Sc. and Ph.D.) students studying epigenetics in conventional, agricultural and medicinal universities. This book will be a useful reference text for teachers and researcher in any discipline of life sciences, agricultural sciences, medicine, and biotechnology.

Big Data in Omics and Imaging

Big Data in Omics and Imaging PDF 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.

The Epigenetics Revolution

The Epigenetics Revolution PDF Author: Nessa Carey
Publisher: Columbia University Press
ISBN: 0231530714
Category : Science
Languages : en
Pages : 353

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Book Description
Epigenetics can potentially revolutionize our understanding of the structure and behavior of biological life on Earth. It explains why mapping an organism's genetic code is not enough to determine how it develops or acts and shows how nurture combines with nature to engineer biological diversity. Surveying the twenty-year history of the field while also highlighting its latest findings and innovations, this volume provides a readily understandable introduction to the foundations of epigenetics. Nessa Carey, a leading epigenetics researcher, connects the field's arguments to such diverse phenomena as how ants and queen bees control their colonies; why tortoiseshell cats are always female; why some plants need cold weather before they can flower; and how our bodies age and develop disease. Reaching beyond biology, epigenetics now informs work on drug addiction, the long-term effects of famine, and the physical and psychological consequences of childhood trauma. Carey concludes with a discussion of the future directions for this research and its ability to improve human health and well-being.

Psychiatric Genetics

Psychiatric Genetics PDF Author: Thomas G. Schulze
Publisher: Oxford University Press
ISBN: 0190221976
Category : Medical
Languages : en
Pages : 241

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Book Description
Psychiatric Genetics: A Primer for Clinical and Basic Scientists offers a straightforward introduction to the essentials of psychiatric genetics, covering basic epidemiology, recruitment for human studies, phenotyping strategies, formal genetic and molecular genetic studies, statistical genetics, bioinformatics and genomics, pharmacogenetics, the most relevant animal models, and biobanking. Each chapter begins with a list of "take home" points that summarizes content, followed by a brief overview of current knowledge and suggestions for further reading.

Systems Genetics

Systems Genetics PDF Author: Florian Markowetz
Publisher: Cambridge University Press
ISBN: 131638098X
Category : Science
Languages : en
Pages : 287

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Book Description
Whereas genetic studies have traditionally focused on explaining heritance of single traits and their phenotypes, recent technological advances have made it possible to comprehensively dissect the genetic architecture of complex traits and quantify how genes interact to shape phenotypes. This exciting new area has been termed systems genetics and is born out of a synthesis of multiple fields, integrating a range of approaches and exploiting our increased ability to obtain quantitative and detailed measurements on a broad spectrum of phenotypes. Gathering the contributions of leading scientists, both computational and experimental, this book shows how experimental perturbations can help us to understand the link between genotype and phenotype. A snapshot of current research activity and state-of-the-art approaches to systems genetics are provided, including work from model organisms such as Saccharomyces cerevisiae and Drosophila melanogaster, as well as from human studies.