Download or read book Whole genome Prediction of Complex Traits Using Kernel Methods written by and published by . This book was released on 2014 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prediction of genetic values has been a focus of quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fuelled by post-Sanger sequencing technologies and especially molecular markers, have driven researchers to extend Fisher's infinitesimal model to confront newly arising challenges. In particular, kernel methods are gaining attention as the regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by genomic regions working in concert with others, thus generating interactions. Motivated by this fact, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This thesis centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We investigated various kernel-based approaches tailored to capturing total genetic variation, to arrive at an enhanced predictive performance of complex traits in the light of available genome annotation information. In particular, this thesis reports on three studies conducted using kernel methods. In the first study using dairy cattle and wheat data, we constructed a diffusion kernel and compared its predictive performance against that of a Gaussian kernel. The second study evaluated some parametric and nonparametric kernels for predicting pre-corrected phenotypes and progeny tests in dairy cow health traits. The third study partitioned SNPs based on annotation and examined sources of predictive performance of complex traits in broiler chickens. Overall, while we obtained some encouraging results with non-parametric kernels, recovering non-additive genetic variation in a validation dataset still remains an ongoing challenge in quantitative genetics.
Download or read book Genomic Prediction for Quantitative Traits written by Ulrike Ober and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Genomic Prediction of Complex Traits written by Nourollah Ahmadi and published by Springer Nature. This book was released on 2022-04-22 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume explores the conceptual framework and the practical issues related to genomic prediction of complex traits in human medicine and in animal and plant breeding. The book is organized into five parts. Part One reminds molecular genetics approaches intending to predict phenotypic variations. Part Two presents the principles of genomic prediction of complex traits, and reviews factors that affect its reliability. Part Three describes genomic prediction methods, including machine-learning approaches, accounting for different degree of biological complexity, and reviews the associated computer-packages. Part Four reports on emerging trends such as phenomic prediction and incorporation into genomic prediction models of “omics” data and crop growth models. Part Five is dedicated to lessons learned from cases studies in the fields of human health and animal and plant breeding, and to methods for analysis of the economic effectiveness of genomic prediction. Written in the highly successful Methods in Molecular Biology series format, the book provides theoretical bases and practical guidelines for an informed decision making of practitioners and identifies pertinent routes for further methodological researches. Cutting-edge and thorough, Complex Trait Predictions: Methods and Protocols is a valuable resource for scientists and researchers who are interested in learning more about this important and developing field. Chapters 3, 9, 13, 14, and 21 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Download or read book PREDICTION OF COMPLEX TRAITS USING GENOMIC DATA written by GUSTAVO. DE LOS CAMPOS and published by . This book was released on 2023 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Kernel Methods for Pattern Analysis written by John Shawe-Taylor and published by Cambridge University Press. This book was released on 2004-06-28 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher Description
Download or read book Neural Networks in Finance and Investing written by Robert R. Trippi and published by Irwin Professional Publishing. This book was released on 1996 with total page 872 pages. Available in PDF, EPUB and Kindle. Book excerpt: This completely updated version of the classic first edition offers a wealth of new material reflecting the latest developments in teh field. For investment professionals seeking to maximize this exciting new technology, this handbook is the definitive information source.
Download or read book Multivariate Statistical Machine Learning Methods for Genomic Prediction written by Osval Antonio Montesinos López and published by Springer Nature. This book was released on 2022-02-14 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.
Download or read book Use of Whole genome Sequence Data for Genomic Prediction Across Populations and Species written by and published by . This book was released on 2020 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Genome wide association studies and genomic selection for crop improvement in the era of big data written by Nunzio D’Agostino and published by Frontiers Media SA. This book was released on 2023-05-05 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Genome Wide Association Studies and Genomic Prediction written by Cedric Gondro and published by Humana Press. This book was released on 2013-06-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the detailed genomic information that is now becoming available, we have a plethora of data that allows researchers to address questions in a variety of areas. Genome-wide association studies (GWAS) have become a vital approach to identify candidate regions associated with complex diseases in human medicine, production traits in agriculture, and variation in wild populations. Genomic prediction goes a step further, attempting to predict phenotypic variation in these traits from genomic information. Genome-Wide Association Studies and Genomic Prediction pulls together expert contributions to address this important area of study. The volume begins with a section covering the phenotypes of interest as well as design issues for GWAS, then moves on to discuss efficient computational methods to store and handle large datasets, quality control measures, phasing, haplotype inference, and imputation. Later chapters deal with statistical approaches to data analysis where the experimental objective is either to confirm the biology by identifying genomic regions associated to a trait or to use the data to make genomic predictions about a future phenotypic outcome (e.g. predict onset of disease). As part of the Methods in Molecular Biology series, chapters provide helpful, real-world implementation advice.
Download or read book Bayesian Methods in Structural Bioinformatics written by Thomas Hamelryck and published by Springer. This book was released on 2012-03-23 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an edited volume, the goal of which is to provide an overview of the current state-of-the-art in statistical methods applied to problems in structural bioinformatics (and in particular protein structure prediction, simulation, experimental structure determination and analysis). It focuses on statistical methods that have a clear interpretation in the framework of statistical physics, rather than ad hoc, black box methods based on neural networks or support vector machines. In addition, the emphasis is on methods that deal with biomolecular structure in atomic detail. The book is highly accessible, and only assumes background knowledge on protein structure, with a minimum of mathematical knowledge. Therefore, the book includes introductory chapters that contain a solid introduction to key topics such as Bayesian statistics and concepts in machine learning and statistical physics.
Download or read book Crop Development Growth and Yield written by Lancaster Mason and published by . This book was released on 2019-06-12 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of crop development, growth and yield falls under the domain of agricultural science. It focuses on ways to increase crop yield through the right use of fertilizers and pesticides. A good crop production management system addresses both crop production optimization and environmental sustainability. Research in crop science involves developing strategies for improving cultivars, crop yield, disease resistance and climate resilience. The field also uses tools of biotechnology and genetic engineering in order to alter the genetic traits of crops and to produce a better quality yield. This book is a compilation of chapters that discuss the most vital concepts and emerging trends in the field of crop development, growth and yield. It provides a comprehensive understanding of modern theories and advanced concepts of this field. This book will serve as a reference to a broad spectrum of readers.
Download or read book Wheat Landraces written by Nusret Zencirci and published by Springer Nature. This book was released on 2021-09-15 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Landraces possess a very large genetic base in population structure and are dynamic populations of cultivated plants with historical origin, distinct identity, and without any formal crop improvement. They are often genetically diverse, locally adapted, and associated with traditional farming systems. Resistance genes to biotic and abiotic stress factors, which are especially diversified in landraces, are of great interest to plant breeders, faced with global climate challenge. In addition, gene pools made of different landraces grown in different ecological conditions can be used for wheat breeding to enhance quality; yield and other desirable agricultural parameters. An estimated 75% of the genetic diversity of crop plants was lost in the last century due to the replacement of high yielding modern varieties. There is, thus, an urgent need to preserve existing species, not only for posterity but also as a means to secure food supply for a rising world population. In this book, we provide an overview of wheat landraces with special attention to genetic diversities, conservation, and utilization.
Download or read book Lipids in Photosynthesis written by Hajime Wada and published by Springer Science & Business Media. This book was released on 2009-11-07 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lipids in Photosynthesis: Essential and Regulatory Functions, provides an essential summary of an exciting decade of research on relationships between lipids and photosynthesis. The book brings together extensively cross-referenced and peer-reviewed chapters by prominent researchers. The topics covered include the structure, molecular organization and biosynthesis of fatty acids, glycerolipids and nonglycerolipids in plants, algae, lichens, mosses, and cyanobacteria, as well as in chloroplasts and mitochondria. Several chapters deal with the manipulation of the extent of unsaturation of fatty acids and the effects of such manipulation on photosynthesis and responses to various forms of stress. The final chapters focus on lipid trafficking, signaling and advanced analytical techniques. Ten years ago, Siegenthaler and Murata edited "Lipids in Photosynthesis: Structure, Function and Genetics," which became a classic in the field. "Lipids in Photosynthesis: Essential and Regulatory Functions," belongs, with its predecessor, in every plant and microbiological researcher's bookcase.
Download or read book Genetic Data Analysis for Plant and Animal Breeding written by Fikret Isik and published by Springer. This book was released on 2017-09-09 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book fills the gap between textbooks of quantitative genetic theory, and software manuals that provide details on analytical methods but little context or perspective on which methods may be most appropriate for a particular application. Accordingly this book is composed of two sections. The first section (Chapters 1 to 8) covers topics of classical phenotypic data analysis for prediction of breeding values in animal and plant breeding programs. In the second section (Chapters 9 to 13) we provide the concept and overall review of available tools for using DNA markers for predictions of genetic merits in breeding populations. With advances in DNA sequencing technologies, genomic data, especially single nucleotide polymorphism (SNP) markers, have become available for animal and plant breeding programs in recent years. Analysis of DNA markers for prediction of genetic merit is a relatively new and active research area. The algorithms and software to implement these algorithms are changing rapidly. This section represents state-of-the-art knowledge on the tools and technologies available for genetic analysis of plants and animals. However, readers should be aware that the methods or statistical packages covered here may not be available or they might be out of date in a few years. Ultimately the book is intended for professional breeders interested in utilizing these tools and approaches in their breeding programs. Lastly, we anticipate the usage of this volume for advanced level graduate courses in agricultural and breeding courses.
Download or read book Genetics written by Daniel L. Hartl and published by Jones & Bartlett Publishers. This book was released on 2012 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Plant Breeding Past Present and Future written by John E. Bradshaw and published by Springer. This book was released on 2016-03-08 with total page 710 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
