Quantitative Genetics And Its Connections With Big Data And Sequenced Genomes

Author : Charles J Mode
Publisher : World Scientific Publishing Company
Page : 180 pages
File Size : 41,8 Mb
Release : 2016-11-02
Category : Electronic
ISBN : 9789813140707

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Quantitative Genetics and Its Connections with Big Data and Sequenced Genomes by Charles J Mode Pdf

The book gives an overview of developments in Quantitative Genetics and variance component analysis in an era of Big Data and Sequenced Genomes. It provides a detailed description of a direct method of estimation that will be a useful means of extracting information from a large set of data that was inconceivable 10 to 20 years ago. The book is a combination of a history of variance component analysis and a forward looking view as to how direct methods of estimation arise from the availability of big data sets and sequenced genomes of each individual in the sample. Many papers and books on quantitative genetics versions of the general linear model from statistics are useful for analyzing the data, using relatively small sets of data. In this book, new methods of direct estimation are introduced and analyzed that are appropriate for an era of big sets of data and sequences genomes. These direct methods of estimation are based on taking conditional expectations rather the methods of least squares that characterize many applications of the general linear model of statistics. Request Inspection Copy

Author : Charles J. Mode
Publisher : Unknown
Page : 179 pages
File Size : 42,8 Mb
Release : 2016
Category : Electronic
ISBN : 9813140690

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Quantitative Genetics and Its Connections with Big Data and Sequenced Genomes by Charles J. Mode Pdf

Author : Ka-Chun Wong
Publisher : Springer
Page : 428 pages
File Size : 43,7 Mb
Release : 2016-10-24
Category : Computers
ISBN : 9783319412795

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Big Data Analytics in Genomics by Ka-Chun Wong Pdf

This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at an unprecedented pace. To reveal novel genomic insights from this data within a reasonable time frame, traditional data analysis methods may not be sufficient or scalable, forcing the need for big data analytics to be developed for genomics. The computational methods addressed in the book are intended to tackle crucial biological questions using big data, and are appropriate for either newcomers or veterans in the field.This volume offers thirteen peer-reviewed contributions, written by international leading experts from different regions, representing Argentina, Brazil, China, France, Germany, Hong Kong, India, Japan, Spain, and the USA. In particular, the book surveys three main areas: statistical analytics, computational analytics, and cancer genome analytics. Sample topics covered include: statistical methods for integrative analysis of genomic data, computation methods for protein function prediction, and perspectives on machine learning techniques in big data mining of cancer. Self-contained and suitable for graduate students, this book is also designed for bioinformaticians, computational biologists, and researchers in communities ranging from genomics, big data, molecular genetics, data mining, biostatistics, biomedical science, cancer research, medical research, and biology to machine learning and computer science. Readers will find this volume to be an essential read for appreciating the role of big data in genomics, making this an invaluable resource for stimulating further research on the topic.

Author : Manjit S. Kang
Publisher : CABI
Page : 433 pages
File Size : 47,6 Mb
Release : 2020-04-01
Category : Science
ISBN : 9781789240214

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Quantitative Genetics, Genomics and Plant Breeding, 2nd Edition by Manjit S. Kang Pdf

This book presents state-of-the-art, authoritative chapters on contemporary issues in the broad areas of quantitative genetics, genomics and plant breeding. Section 1 (Chapters 2 to 12) emphasizes the application of genomics, and genome and epigenome editing techniques, in plant breeding; bioinformatics; quantitative trait loci mapping; and the latest approaches of examining and exploiting genotype-environment interactions. Section 2 (Chapters 13 to 20) represents the intersection of breeding, genetics and genomics. This section describes the use of cutting-edge molecular breeding and quantitative genetics techniques in wheat, rice, maize, root and tuber crops and pearl millet. Overall, the book focuses on using genomic information to help evaluate traits that can combat biotic/abiotic stresses, genome-wide association mapping, high-throughput genotyping/phenotyping, biofortification, use of big data, orphan crops, and gene editing techniques. The examples featured are taken from across crop science research and cover a wide geographical base.

Author : Momiao Xiong
Publisher : CRC Press
Page : 668 pages
File Size : 51,8 Mb
Release : 2017-12-01
Category : Mathematics
ISBN : 9781498725804

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Big Data in Omics and Imaging by Momiao Xiong Pdf

Big Data in Omics and Imaging: Association Analysis addresses the recent development of association analysis and machine learning for both population and family genomic data in sequencing era. It is unique in that it presents both hypothesis testing and a data mining approach to holistically dissecting the genetic structure of complex traits and to designing efficient strategies for precision medicine. The general frameworks for association analysis and machine learning, developed in the text, can be applied to genomic, epigenomic and imaging data. FEATURES Bridges the gap between the traditional statistical methods and computational tools for small genetic and epigenetic data analysis and the modern advanced statistical methods for big data Provides tools for high dimensional data reduction Discusses searching algorithms for model and variable selection including randomization algorithms, Proximal methods and matrix subset selection Provides real-world examples and case studies Will have an accompanying website with R code The book is designed for graduate students and researchers in genomics, bioinformatics, and data science. It represents the paradigm shift of genetic studies of complex diseases– from shallow to deep genomic analysis, from low-dimensional to high dimensional, multivariate to functional data analysis with next-generation sequencing (NGS) data, and from homogeneous populations to heterogeneous population and pedigree data analysis. Topics covered are: advanced matrix theory, convex optimization algorithms, generalized low rank models, functional data analysis techniques, deep learning principle and machine learning methods for modern association, interaction, pathway and network analysis of rare and common variants, biomarker identification, disease risk and drug response prediction.

Author : Anonim
Publisher : DIANE Publishing
Page : 215 pages
File Size : 50,5 Mb
Release : 1988
Category : Gene mapping
ISBN : 9781428922587

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Mapping our genes : the genome projects : how big, how fast? by Anonim Pdf

Author : Altuna Akalin
Publisher : CRC Press
Page : 462 pages
File Size : 55,9 Mb
Release : 2020-12-16
Category : Mathematics
ISBN : 9781498781862

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Computational Genomics with R by Altuna Akalin Pdf

Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.

Author : Emmanuel Paradis
Publisher : CRC Press
Page : 313 pages
File Size : 46,8 Mb
Release : 2020-03-13
Category : Mathematics
ISBN : 9780429882425

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Population Genomics with R by Emmanuel Paradis Pdf

Population Genomics With R presents a multidisciplinary approach to the analysis of population genomics. The methods treated cover a large number of topics from traditional population genetics to large-scale genomics with high-throughput sequencing data. Several dozen R packages are examined and integrated to provide a coherent software environment with a wide range of computational, statistical, and graphical tools. Small examples are used to illustrate the basics and published data are used as case studies. Readers are expected to have a basic knowledge of biology, genetics, and statistical inference methods. Graduate students and post-doctorate researchers will find resources to analyze their population genetic and genomic data as well as help them design new studies. The first four chapters review the basics of population genomics, data acquisition, and the use of R to store and manipulate genomic data. Chapter 5 treats the exploration of genomic data, an important issue when analysing large data sets. The other five chapters cover linkage disequilibrium, population genomic structure, geographical structure, past demographic events, and natural selection. These chapters include supervised and unsupervised methods, admixture analysis, an in-depth treatment of multivariate methods, and advice on how to handle GIS data. The analysis of natural selection, a traditional issue in evolutionary biology, has known a revival with modern population genomic data. All chapters include exercises. Supplemental materials are available on-line (http://ape-package.ird.fr/PGR.html).

Author : Momiao Xiong
Publisher : CRC Press
Page : 404 pages
File Size : 42,9 Mb
Release : 2017-12-01
Category : Mathematics
ISBN : 9781315353418

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Big Data in Omics and Imaging by Momiao Xiong Pdf

Big Data in Omics and Imaging: Association Analysis addresses the recent development of association analysis and machine learning for both population and family genomic data in sequencing era. It is unique in that it presents both hypothesis testing and a data mining approach to holistically dissecting the genetic structure of complex traits and to designing efficient strategies for precision medicine. The general frameworks for association analysis and machine learning, developed in the text, can be applied to genomic, epigenomic and imaging data. FEATURES Bridges the gap between the traditional statistical methods and computational tools for small genetic and epigenetic data analysis and the modern advanced statistical methods for big data Provides tools for high dimensional data reduction Discusses searching algorithms for model and variable selection including randomization algorithms, Proximal methods and matrix subset selection Provides real-world examples and case studies Will have an accompanying website with R code The book is designed for graduate students and researchers in genomics, bioinformatics, and data science. It represents the paradigm shift of genetic studies of complex diseases– from shallow to deep genomic analysis, from low-dimensional to high dimensional, multivariate to functional data analysis with next-generation sequencing (NGS) data, and from homogeneous populations to heterogeneous population and pedigree data analysis. Topics covered are: advanced matrix theory, convex optimization algorithms, generalized low rank models, functional data analysis techniques, deep learning principle and machine learning methods for modern association, interaction, pathway and network analysis of rare and common variants, biomarker identification, disease risk and drug response prediction.

Author : Anonim
Publisher : Unknown
Page : 228 pages
File Size : 55,5 Mb
Release : 1988
Category : Biotechnology
ISBN : UCR:31210010367827

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Mapping Our Genes by Anonim Pdf

Author : John E. Bradshaw
Publisher : Springer
Page : 693 pages
File Size : 47,8 Mb
Release : 2016-03-08
Category : Science
ISBN : 9783319232850

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Plant Breeding: Past, Present and Future by John E. Bradshaw Pdf

This book aims to help plant breeders by reviewing past achievements, currently successful practices, and emerging methods and techniques. Theoretical considerations are also presented to strike the right balance between being as simple as possible but as complex as necessary. The United Nations predicts that the global human population will continue rising to 9.0 billion by 2050. World food production will need to increase between 70-100 per cent in just 40 years. First generation bio-fuels are also using crops and cropland to produce energy rather than food. In addition, land area used for agriculture may remain static or even decrease as a result of degradation and climate change, despite more land being theoretically available, unless crops can be bred which tolerate associated abiotic stresses. Lastly, it is unlikely that steps can be taken to mitigate all of the climate change predicted to occur by 2050, and beyond, and hence adaptation of farming systems and crop production will be required to reduce predicted negative effects on yields that will occur without crop adaptation. Substantial progress will therefore be required in bridging the yield gap between what is currently achieved per unit of land and what should be possible in future, with the best farming methods and best storage and transportation of food, given the availability of suitably adapted cultivars, including adaptation to climate change. My book is divided into four parts: Part I is an historical introduction; Part II deals with the origin of genetic variation by mutation and recombination of DNA; Part III explains how the mating system of a crop species determines the genetic structure of its landraces; Part IV considers the three complementary options for future progress: use of sexual reproduction in further conventional breeding, base broadening and introgression; mutation breeding; and genetically modified crops.

Author : Kuo Ping Chiu
Publisher : Bentham Science Publishers
Page : 160 pages
File Size : 42,5 Mb
Release : 2015-11-04
Category : Science
ISBN : 9781681080925

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Next-Generation Sequencing and Sequence Data Analysis by Kuo Ping Chiu Pdf

Nucleic acid sequencing techniques have enabled researchers to determine the exact order of base pairs - and by extension, the information present - in the genome of living organisms. Consequently, our understanding of this information and its link to genetic expression at molecular and cellular levels has lead to rapid advances in biology, genetics, biotechnology and medicine. Next-Generation Sequencing and Sequence Data Analysis is a brief primer on DNA sequencing techniques and methods used to analyze sequence data. Readers will learn about recent concepts and methods in genomics such as sequence library preparation, cluster generation for PCR technologies, PED sequencing, genome assembly, exome sequencing, transcriptomics and more. This book serves as a textbook for students undertaking courses in bioinformatics and laboratory methods in applied biology. General readers interested in learning about DNA sequencing techniques may also benefit from the simple format of information presented in the book.

Author : National Academies of Sciences, Engineering, and Medicine,Division on Earth and Life Studies,Board on Life Sciences
Publisher : National Academies Press
Page : 201 pages
File Size : 40,8 Mb
Release : 2020-12-18
Category : Science
ISBN : 9780309676731

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Next Steps for Functional Genomics by National Academies of Sciences, Engineering, and Medicine,Division on Earth and Life Studies,Board on Life Sciences Pdf

One of the holy grails in biology is the ability to predict functional characteristics from an organism's genetic sequence. Despite decades of research since the first sequencing of an organism in 1995, scientists still do not understand exactly how the information in genes is converted into an organism's phenotype, its physical characteristics. Functional genomics attempts to make use of the vast wealth of data from "-omics" screens and projects to describe gene and protein functions and interactions. A February 2020 workshop was held to determine research needs to advance the field of functional genomics over the next 10-20 years. Speakers and participants discussed goals, strategies, and technical needs to allow functional genomics to contribute to the advancement of basic knowledge and its applications that would benefit society. This publication summarizes the presentations and discussions from the workshop.

Author : George P. Patrinos
Publisher : Academic Press
Page : 406 pages
File Size : 44,6 Mb
Release : 2019-11-13
Category : Science
ISBN : 9780128136966

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Applied Genomics and Public Health by George P. Patrinos Pdf

Applied Genomics and Public Health examines the interdisciplinary and growing area of how evidence-based genomic knowledge can be applied to public health, population health, healthcare and health policies. The book gathers experts from a variety of disciplines, including life sciences, social sciences, and health care to develop a comprehensive overview of the field. In addition, the book delves into subjects such as pharmacogenomics, genethics, big data, data translation and analysis, economic evaluation, genomic awareness and education, sociology, pricing and reimbursement, policy measures and economic evaluation in genomic medicine. This book is essential reading for researchers and students exploring applications of genomics to population and public health. In addition, it is ideal for those in the biomedical sciences, medical sociologists, healthcare professionals, nurses, regulatory bodies and health economists interested in learning more about this growing field. Explores the growing application of genomics to population and public health Features internationally renowned contributors from a variety of related fields Contains chapters on important topics such as genomic data sharing, genethics and public health genomics, genomics and sociology, and regulatory aspects of genomic medicine and pharmacogenomics

Author : Nunzio D’Agostino,Alison Bentley,Charles Chen
Publisher : Frontiers Media SA
Page : 192 pages
File Size : 43,6 Mb
Release : 2023-05-05
Category : Science
ISBN : 9782889763382

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Genome wide association studies and genomic selection for crop improvement in the era of big data by Nunzio D’Agostino,Alison Bentley,Charles Chen Pdf