Multivariate Statistical Machine Learning Methods For Genomic Prediction
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| Author | : Osval Antonio Montesinos López |
| Publisher | : Springer Nature |
| Total Pages | : 707 |
| Release | : 2022-02-14 |
| Genre | : Technology & Engineering |
| ISBN | : 3030890104 |
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.
| Author | : Vikas Khullar |
| Publisher | : CRC Press |
| Total Pages | : 294 |
| Release | : 2024-01-22 |
| Genre | : Computers |
| ISBN | : 1003825591 |
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.
| Author | : Galety, Mohammad Gouse |
| Publisher | : IGI Global |
| Total Pages | : 359 |
| Release | : 2024-04-29 |
| Genre | : Technology & Engineering |
| ISBN | : |
In geospatial analysis, navigating the complexities of data interpretation and analysis presents a formidable challenge. Traditional methods often need to efficiently handle vast volumes of geospatial data while providing insightful and actionable results. Scholars and practitioners grapple with manual or rule-based approaches, hindering progress in understanding and addressing pressing issues such as climate change, urbanization, and resource management. Ethics, Machine Learning, and Python in Geospatial Analysis offers a solution to the challenges faced by leveraging the extensive library support and user-friendly interface of Python and machine learning. The book’s meticulously crafted chapters guide readers through the intricacies of Python programming and its application in geospatial analysis, from fundamental concepts to advanced techniques.
| Author | : Vijay Rani Rajpal |
| Publisher | : Frontiers Media SA |
| Total Pages | : 312 |
| Release | : 2023-07-10 |
| Genre | : Science |
| ISBN | : 2832528112 |
| Author | : |
| Publisher | : Elsevier |
| Total Pages | : 320 |
| Release | : 2024-02-01 |
| Genre | : Technology & Engineering |
| ISBN | : 0443295255 |
Advances in Agronomy, Volume 184, the latest release in this leading reference on agronomy, contains a variety of updates and highlights new advances in the field. Each chapter is written by an international board of authors, with this new release including new chapters on The Role of Artificial Intelligence in Crop Improvement, Dealing with the Impact of Climate Change-Induced Drought on the Management of Soil, Challenges and Emerging Opportunities of Weed Management in Organic Agriculture, The Broadbalk Wheat Experiment, Rothamsted, UK: Crop Yields and Soil Changes During the Last 50 Years. Includes numerous, timely, state-of-the-art reviews on the latest advancements in agronomy Features distinguished, well recognized authors from around the world Builds upon this venerable and iconic review series Covers the extensive variety and breadth of subject matter in the crop and soil sciences
| Author | : Srivastava, Pramod Kumar |
| Publisher | : IGI Global |
| Total Pages | : 315 |
| Release | : 2024-03-22 |
| Genre | : Computers |
| ISBN | : |
Technology is constantly evolving, and machine learning is positioned to become a pivotal tool with the power to transform industries and revolutionize everyday life. This book underscores the urgency of leveraging the latest machine learning methodologies and theoretical advancements, all while harnessing a wealth of realistic data and affordable computational resources. Machine learning is no longer confined to theoretical domains; it is now a vital component in healthcare, manufacturing, education, finance, law enforcement, and marketing, ushering in an era of data-driven decision-making. Academic scholars seeking to unlock the potential of machine learning in the context of Industry 5.0 and advanced IoT applications will find that the groundbreaking book, Methodologies, Frameworks, and Applications of Machine Learning, introduces an unmissable opportunity to delve into the forefront of modern research and application. This book offers a wealth of knowledge and practical insights across a wide array of topics, ranging from conceptual frameworks and methodological approaches to the application of probability theory, statistical techniques, and machine learning in domains as diverse as e-government, healthcare, cyber-physical systems, and sustainable development, this comprehensive guide equips you with the tools to navigate the complexities of Industry 5.0 and the Internet of Things (IoT).
| Author | : Jen-Tsung Chen |
| Publisher | : John Wiley & Sons |
| Total Pages | : 612 |
| Release | : 2024-07-22 |
| Genre | : Science |
| ISBN | : 1394209959 |
Explore and advance bioinformatics and systems biology tools for crop breeding programs in this practical resource for researchers Plant biology and crop breeding have produced an immense amount of data in recent years, from genomics to interactome and beyond. Bioinformatics tools, which aim at analyzing the vast quantities of data produced by biological research and processes, have developed at a rapid pace to meet the challenges of this vast data trove. The resulting field of bioinformatics and systems biology is producing increasingly rich and transformative research. Bioinformatics for Plant Research and Crop Breeding offers an overview of this field, its recent advances, and its wider applications. Drawing on a range of analytical and data-science tools, its foundation on an in-silico platform acquired multi-omics makes it indispensable for scientists and researchers alike. It promises to become ever more relevant as new techniques for generating and organizing data continue to transform the field. Bioinformatics for Plant Research and Crop Breeding readers will also find: A focus on emerging trends in plant science, sustainable agriculture, and global food security Detailed discussion of topics including plant diversity, plant stresses, nanotechnology in agriculture, and many others Applications incorporating artificial intelligence, machine learning, deep learning and more Bioinformatics for Plant Research and Crop Breeding is ideal for researchers and scientists interested in the potential of OMICs, and bioinformatic tools to aid and develop crop improvement programs.
| Author | : Walid A. Zgallai |
| Publisher | : Elsevier |
| Total Pages | : 437 |
| Release | : 2024-01-18 |
| Genre | : Science |
| ISBN | : 0323954634 |
Artificial Intelligence and Image Processing in Medical Imaging deals with the applications of processing medical images with a view of improving the quality of the data in order to facilitate better decision- making. The book covers the basics of medical imaging and the fundamentals of image processing. It explains spatial and frequency domain applications of image processing, introduces image compression techniques and their applications, and covers image segmentation techniques and their applications. The book includes object detection and classification applications and provides an overall background to statistical analysis in biomedical systems. The role of Machine Learning, including Neural Networks, Deep Learning, and the implications of the expansion of artificial intelligence is also covered. With contributions from prominent researchers worldwide, this book provides up-to-date and comprehensive coverage of AI applications in image processing where readers will find the latest information with clear examples and illustrations. Provides the latest comprehensive coverage of the developments of AI techniques and the principles of medical imaging Covers all aspects of medical imaging, from acquisition, the use of hardware and software, image analysis and implementation of AI in problem solving Provides examples of medical imaging and how they’re processed, including segmentation, classification, and detection
| Author | : Euclid Seeram |
| Publisher | : Springer Nature |
| Total Pages | : 222 |
| Release | : |
| Genre | : |
| ISBN | : 3031640497 |
| Author | : Sanjiban Sekhar Roy |
| Publisher | : Springer Nature |
| Total Pages | : 222 |
| Release | : 2022-06-23 |
| Genre | : Technology & Engineering |
| ISBN | : 9811691584 |
Currently, machine learning is playing a pivotal role in the progress of genomics. The applications of machine learning are helping all to understand the emerging trends and the future scope of genomics. This book provides comprehensive coverage of machine learning applications such as DNN, CNN, and RNN, for predicting the sequence of DNA and RNA binding proteins, expression of the gene, and splicing control. In addition, the book addresses the effect of multiomics data analysis of cancers using tensor decomposition, machine learning techniques for protein engineering, CNN applications on genomics, challenges of long noncoding RNAs in human disease diagnosis, and how machine learning can be used as a tool to shape the future of medicine. More importantly, it gives a comparative analysis and validates the outcomes of machine learning methods on genomic data to the functional laboratory tests or by formal clinical assessment. The topics of this book will cater interest to academicians, practitioners working in the field of functional genomics, and machine learning. Also, this book shall guide comprehensively the graduate, postgraduates, and Ph.D. scholars working in these fields.
