Multivariate Statistical Machine Learning Methods For Genomic Prediction
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Multivariate Statistical Machine Learning Methods for Genomic Prediction
Author: Osval Antonio Montesinos López
language: en
Publisher: Springer Nature
Release Date: 2022-02-14
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.
Artificial Intelligence and Society 5.0
The artificial intelligence-based framework, algorithms, and applications presented in this book take the perspective of Society 5.0 – a social order supported by innovation in data, information, and knowledge. It showcases current case studies of Society 5.0 in diverse areas such as healthcare, smart cities, and infrastructure. Key Features: Elaborates on the use of big data, cyber-physical systems, robotics, augmented-virtual reality, and cybersecurity as pillars for Society 5.0. Showcases the use of artificial intelligence, architecture, frameworks, and distributed and federated learning structures in Society 5.0. Discusses speech recognition, image classification, robotic process automation, natural language generation, and decision support automation. Elucidates the application of machine learning, deep learning, fuzzy-based systems, and natural language processing. Includes case studies on the application of Society 5.0 aspects in educational, medical, infrastructure, and smart cities. The book is intendended especially for graduate and postgraduate students, and academic researchers in the fields of computer science and engineering, electrical engineering, and information technology.
Insights in Functional and Applied Plant Genomics: 2023
We are now entering the third decade of the 21st Century, and, especially in the last years, the achievements made by scientists have been exceptional, leading to major advancements in the fast-growing field of plant science. Frontiers has organized a series of Research Topics to highlight the latest advancements in research across the field of plant science, with articles from the Associate Members of our accomplished Editorial Boards. This editorial initiative of particular relevance, led by Dr. Huihui Li, Specialty Chief Editor of the Functional and Applied Plant Genomics section, is focused on new insights, novel developments, current challenges, latest discoveries, recent advances, and future perspectives in the field of Functional and Applied Plant Genomics. The Research Topic solicits brief, forward-looking contributions from the editorial board members that describe the state of the art, outlining, recent developments and major accomplishments that have been achieved and that need to occur to move the field forward. Authors are encouraged to identify the greatest challenges in the sub-disciplines, and how to address those challenges. The goal of this special edition Research Topic is to shed light on the progress made in the past decade in the field of Functional and Applied Plant Genomics, and on its future challenges to provide a thorough overview of the field. This article collection will inspire, inform and provide direction and guidance to researchers in the field. We welcome original research, reviews, perspective, and thought-provoking opinion to this Research Topic.