Meta Analysis And Combining Information In Genetics And Genomics
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Meta-analysis and Combining Information in Genetics and Genomics by Rudy Guerra,Darlene R. Goldstein Pdf
Novel Techniques for Analyzing and Combining Data from Modern Biological StudiesBroadens the Traditional Definition of Meta-AnalysisWith the diversity of data and meta-data now available, there is increased interest in analyzing multiple studies beyond statistical approaches of formal meta-analysis. Covering an extensive range of quantitative infor
Meta-analysis and Combining Information in Genetics and Genomics by Rudy Guerra,Darlene R. Goldstein Pdf
Novel Techniques for Analyzing and Combining Data from Modern Biological Studies Broadens the Traditional Definition of Meta-Analysis With the diversity of data and meta-data now available, there is increased interest in analyzing multiple studies beyond statistical approaches of formal meta-analysis. Covering an extensive range of quantitative information combination methods, Meta-analysis and Combining Information in Genetics and Genomics looks at how to analyze multiple studies from a broad perspective. After presenting the basic ideas and tools of meta-analysis, the book addresses the combination of similar data types: genotype data from genome-wide linkage scans and data derived from microarray gene expression experiments. The expert contributors show how some data combination problems can arise even within the same basic framework and offer solutions to these problems. They also discuss the combined analysis of different data types, giving readers an opportunity to see data combination approaches in action across a wide variety of genome-scale investigations. As heterogeneous data sets become more common, biological understanding will be significantly aided by jointly analyzing such data using fundamentally sound statistical methodology. This book provides many novel techniques for analyzing data from modern biological studies that involve multiple data sets, either of the same type or multiple data sources.
Assessing Rare Variation in Complex Traits by Eleftheria Zeggini,Andrew Morris Pdf
This book is unique in covering a wide range of design and analysis issues in genetic studies of rare variants, taking advantage of collaboration of the editors with many experts in the field through large-scale international consortia including the UK10K Project, GO-T2D and T2D-GENES. Chapters provide details of state-of-the-art methodology for rare variant detection and calling, imputation and analysis in samples of unrelated individuals and families. The book also covers analytical issues associated with the study of rare variants, such as the impact of fine-scale population structure, and with combining information on rare variants across studies in a meta-analysis framework. Genetic association studies have in the last few years substantially enhanced our understanding of factors underlying traits of high medical importance, such as body mass index, lipid levels, blood pressure and many others. There is growing empirical evidence that low-frequency and rare variants play an important role in complex human phenotypes. This book covers multiple aspects of study design, analysis and interpretation for complex trait studies focusing on rare sequence variation. In many areas of genomic research, including complex trait association studies, technology is in danger of outstripping our capacity to analyse and interpret the vast amounts of data generated. The field of statistical genetics in the whole-genome sequencing era is still in its infancy, but powerful methods to analyse the aggregation of low-frequency and rare variants are now starting to emerge. The chapter Functional Annotation of Rare Genetic Variants is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Computational Hydrodynamics of Capsules and Biological Cells by Constantine Pozrikidis Pdf
Spanning biological, mathematical, computational, and engineering sciences, computational biofluiddynamics addresses a diverse family of problems involving fluid flow inside and around living organisms, organs, tissue, biological cells, and other biological materials. Computational Hydrodynamics of Capsules and Biological Cells provides a comprehensive, rigorous, and current introduction to the fundamental concepts, mathematical formulation, alternative approaches, and predictions of this evolving field. In the first several chapters on boundary-element, boundary-integral, and immersed-boundary methods, the book covers the flow-induced deformation of idealized two-dimensional red blood cells in Stokes flow, capsules with spherical unstressed shapes based on direct and variational formulations, and cellular flow in domains with complex geometry. It also presents simulations of microscopic hemodynamics and hemorheology as well as results on the deformation of capsules and cells in dilute and dense suspensions. The book then describes a discrete membrane model where a surface network of viscoelastic links emulates the spectrin network of the cytoskeleton, before presenting a novel two-dimensional model of red and white blood cell motion. The final chapter discusses the numerical simulation of platelet motion near a wall representing injured tissue. This volume provides a roadmap to the current state of the art in computational cellular mechanics and biofluiddynamics. It also indicates areas for further work on mathematical formulation and numerical implementation and identifies physiological problems that need to be addressed in future research. MATLAB® code and other data are available at http://dehesa.freeshell.org/CC2
Computational Genetics and Genomics by Gary Peltz Pdf
Ultimately, the quality of the tools available for genetic analysis and experimental disease models will be assessed on the basis of whether they provide new information that generates novel treatments for human disease. In addition, the time frame in which genetic discoveries impact clinical practice is also an important dimension of how society assesses the results of the significant public financial investment in genetic research. Because of the investment and the increased expectation that new tre- ments will be found for common diseases, allowing decades to pass before basic discoveries are made and translated into new therapies is no longer acceptable. Computational Genetics and Genomics: Tools for Understanding Disease provides an overview and assessment of currently available and developing tools for genetic analysis. It is hoped that these new tools can be used to identify the genetic basis for susceptibility to disease. Although this very broad topic is addressed in many other books and journal articles, Computational Genetics and Genomics: Tools for Understanding Disease focuses on methods used for analyzing mouse genetic models of biomedically - portant traits. This volume aims to demonstrate that commonly used inbred mouse strains can be used to model virtually all human disea- related traits. Importantly, recently developed computational tools will enable the genetic basis for differences in disease-related traits to be rapidly identified using these inbred mouse strains. On average, a decade is required to carry out the development process required to demonstrate that a new disease treatment is beneficial.
Computational Exome and Genome Analysis by Peter N. Robinson,Rosario Michael Piro,Marten Jager Pdf
Exome and genome sequencing are revolutionizing medical research and diagnostics, but the computational analysis of the data has become an extremely heterogeneous and often challenging area of bioinformatics. Computational Exome and Genome Analysis provides a practical introduction to all of the major areas in the field, enabling readers to develop a comprehensive understanding of the sequencing process and the entire computational analysis pipeline.
Handbook of Statistical Genomics by David J. Balding,Ida Moltke,John Marioni Pdf
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.
Genome Annotation by Jung Soh,Paul M.K. Gordon,Christoph W. Sensen Pdf
The success of individualized medicine, advanced crops, and new and sustainable energy sources requires thoroughly annotated genomic information and the integration of this information into a coherent model. A thorough overview of this field, Genome Annotation explores automated genome analysis and annotation from its origins to the challenges of next-generation sequencing data analysis. The book initially takes you through the last 16 years since the sequencing of the first complete microbial genome. It explains how current analysis strategies were developed, including sequencing strategies, statistical models, and early annotation systems. The authors then present visualization techniques for displaying integrated results as well as state-of-the-art annotation tools, including MAGPIE, Ensembl, Bluejay, and Galaxy. They also discuss the pipelines for the analysis and annotation of complex, next-generation DNA sequencing data. Each chapter includes references and pointers to relevant tools. As very few existing genome annotation pipelines are capable of dealing with the staggering amount of DNA sequence information, new strategies must be developed to accommodate the needs of today’s genome researchers. Covering this topic in detail, Genome Annotation provides you with the foundation and tools to tackle this challenging and evolving area. Suitable for both students new to the field and professionals who deal with genomic information in their work, the book offers two genome annotation systems on an accompanying CD-ROM.
National Research Council,Commission on Behavioral and Social Sciences and Education,Committee on Population
Author : National Research Council,Commission on Behavioral and Social Sciences and Education,Committee on Population Publisher : National Academies Press Page : 388 pages File Size : 46,8 Mb Release : 2001-01-19 Category : Social Science ISBN : 9780309171434
Cells and Surveys by National Research Council,Commission on Behavioral and Social Sciences and Education,Committee on Population Pdf
What can social science, and demography in particular, reasonably expect to learn from biological information? There is increasing pressure for multipurpose household surveys to collect biological data along with the more familiar interviewer-respondent information. Given that recent technical developments have made it more feasible to collect biological information in non-clinical settings, those who fund, design, and analyze survey data need to think through the rationale and potential consequences. This is a concern that transcends national boundaries. Cells and Surveys addresses issues such as which biologic/genetic data should be collected in order to be most useful to a range of social scientists and whether amassing biological data has unintended side effects. The book also takes a look at the various ethical and legal concerns that such data collection entails.
Comparative Genomics by Joao Meidanis,Luay Nakhleh Pdf
This book constitutes the proceedings of the 15th International Workshop Comparative Genomics, RECOMB-CG 2017, held in Barcelona, Spain, in October 2017. The 16 full papers presented were carefully reviewed and selected from 32 submissions. The papers report original research in all areas of Comparative Genomics.
Handbook of Developmental Research Methods by Brett Paul Laursen,Todd D. Little,Noel A. Card Pdf
This is the first methods handbook specifically designed to meet the needs of those studying development. Leading developmental methodologists present cutting-edge analytic tools and describe how and when to use them in accessible, nontechnical language. They also provide valuable guidance for strengthening developmental research with designs that anticipate potential sources of bias. Sections typically begin with an overview chapter on foundational issues. Subsequent chapters delve into specific techniques, following a consistent format that encompasses basic issues, conceptual principles and statistical assumptions, recent technical advances, developmental applications, and future directions. Research examples demonstrate the procedures in action and give readers a better understanding of how to match research questions to developmental methods. The companion website supplies data and program syntax files for many of the chapter examples.
Engineering Genetic Circuits by Chris J. Myers Pdf
An Introduction to Systems Bioengineering Takes a Clear and Systematic Engineering Approach to Systems Biology Focusing on genetic regulatory networks, Engineering Genetic Circuits presents the modeling, analysis, and design methods for systems biology. It discusses how to examine experimental data to learn about mathematical models, develop efficient abstraction and simulation methods to analyze these models, and use analytical methods to guide the design of new circuits. After reviewing the basic molecular biology and biochemistry principles needed to understand genetic circuits, the book describes modern experimental techniques and methods for discovering genetic circuit models from the data generated by experiments. The next four chapters present state-of-the-art methods for analyzing these genetic circuit models. The final chapter explores how researchers are beginning to use analytical methods to design synthetic genetic circuits. This text clearly shows how the success of systems biology depends on collaborations between engineers and biologists. From biomolecular observations to mathematical models to circuit design, it provides essential information on genetic circuits and engineering techniques that can be used to study biological systems.
Topics in Applied Statistics by Mingxiu Hu,Yi Liu,Jianchang Lin Pdf
This volume presents 27 selected papers in topics that range from statistical applications in business and finance to applications in clinical trials and biomarker analysis. All papers feature original, peer-reviewed content. The editors intentionally selected papers that cover many topics so that the volume will serve the whole statistical community and a variety of research interests. The papers represent select contributions to the 21st ICSA Applied Statistics Symposium. The International Chinese Statistical Association (ICSA) Symposium took place between the 23rd and 26th of June, 2012 in Boston, Massachusetts. It was co-sponsored by the International Society for Biopharmaceutical Statistics (ISBS) and American Statistical Association (ASA). This is the inaugural proceedings volume to share research from the ICSA Applied Statistics Symposium.
Biological Knowledge Discovery Handbook by Mourad Elloumi,Albert Y. Zomaya Pdf
The first comprehensive overview of preprocessing, mining,and postprocessing of biological data Molecular biology is undergoing exponential growth in both thevolume and complexity of biological data—and knowledgediscovery offers the capacity to automate complex search and dataanalysis tasks. This book presents a vast overview of the mostrecent developments on techniques and approaches in the field ofbiological knowledge discovery and data mining (KDD)—providingin-depth fundamental and technical field information on the mostimportant topics encountered. Written by top experts, Biological Knowledge DiscoveryHandbook: Preprocessing, Mining, and Postprocessing of BiologicalData covers the three main phases of knowledge discovery (datapreprocessing, data processing—also known as datamining—and data postprocessing) and analyzes both verificationsystems and discovery systems. BIOLOGICAL DATA PREPROCESSING Part A: Biological Data Management Part B: Biological Data Modeling Part C: Biological Feature Extraction Part D Biological Feature Selection BIOLOGICAL DATA MINING Part E: Regression Analysis of Biological Data Part F Biological Data Clustering Part G: Biological Data Classification Part H: Association Rules Learning from Biological Data Part I: Text Mining and Application to Biological Data Part J: High-Performance Computing for Biological DataMining Combining sound theory with practical applications in molecularbiology, Biological Knowledge Discovery Handbook is idealfor courses in bioinformatics and biological KDD as well as forpractitioners and professional researchers in computer science,life science, and mathematics.