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Nutrient Use Efficiency in Plants: Concepts and Approaches is the ninth volume in the Plant Ecophysiology series. It presents a broad overview of topics related to improvement of nutrient use efficiency of crops. Nutrient use efficiency (NUE) is a measure of how well plants use the available mineral nutrients. It can be defined as yield (biomass) per unit input (fertilizer, nutrient content). NUE is a complex trait: it depends on the ability to take up the nutrients from the soil, but also on transport, storage, mobilization, usage within the plant, and even on the environment. NUE is of particular interest as a major target for crop improvement. Improvement of NUE is an essential pre-requisite for expansion of crop production into marginal lands with low nutrient availability but also a way to reduce use of inorganic fertilizer.
Metabolomics – which deals with all metabolites of an organism – is a rapidly-emerging sector of post-genome research fields. It plays significant roles in a variety of fields from medicine to agriculture and holds a fundamental position in functional genomics studies and their application in plant biotechnology. This volume comprehensively covers plant metabolomics for the first time. The chapters offer cutting-edge information on analytical technology, bioinformatics and applications. They were all written by leading researchers who have been directly involved in plant metabolomics research throughout the world. Up-to-date information and future developments are described, thereby producing a volume which is a landmark of plant metabolomics research and a beneficial guideline to graduate students and researchers in academia, industry, and technology transfer organizations in all plant science fields.
Computational and high-throughput methods, such as genomics, proteomics, and transcriptomics, known collectively as “-omics,” have been used to study plant biology for well over a decade now. As these technologies mature, plant and crop scientists have started using these methods to improve crop varieties. Omics in Plant Breeding provides a timely introduction to key omicsbased methods and their application in plant breeding. Omics in Plant Breeding is a practical and accessible overview of specific omics-based methods ranging from metabolomics to phenomics. Covering a single methodology within each chapter, this book provides thorough coverage that ensures a strong understanding of each methodology both in its application to, and improvement of, plant breeding. Accessible to advanced students, researchers, and professionals, Omics in Plant Breeding will be an essential entry point into this innovative and exciting field. • A valuable overview of high-throughput, genomics-based technologies and their applications to plant breeding • Each chapter explores a single methodology, allowing for detailed and thorough coverage • Coverage ranges from well-established methodologies, such as genomics and proteomics, to emerging technologies, including phenomics and physionomics Aluízio Borém is a Professor of Plant Breeding at the University of Viçosa in Brazil. Roberto Fritsche-Neto is a Professor of Genetics and Plant Breeding at the University of São Paulo in Brazil.
This is the newest title in the successful Molecular Plant Biology Handbook Series. Just like the other titles in the series this new book presents an excellent overview of different approaches and techniques in Metabolomics. Contributors are either from ivy-league research institutions or from companies developing new technologies in this dynamic and fast-growing field. With its approach to introduce current techniques in plant metabolomics to a wider audience and with many labs and companies considering to introduce metabolomics for their research, the title meets a growing market. The Kahl books are in addition a trusted brand for the plant science community and have always sold above expectations.
This book provides a comprehensive view of metabolomics, from the basic concepts, through sample preparation and analytical methodologies, to data interpretation and applications in medicine. It is the first volume to cover metabolomics clinical applications while also emphasizing analytical and statistical features. Moreover, future trends and perspectives in clinical metabolomics are also presented. For researches already experienced in metabolomics, the book will be useful as an updated definitive reference. For beginners in the field and graduate students, the book will provide detailed information about concepts and experimental aspects in metabolomics, as well as examples and perspectives of applications of this strategy to clinical questions.
Providing information on the main approaches for the analysis of metabolites, this textbook: Covers basic methodologies in sample preparation and separation techniques, as well as the most recent techniques of mass spectrometry. Differentiates between primary and secondary metabolites. Includes four chapters discussing successful metabolome studies of different organisms. Highlights the analytical challenges of studying metabolites. Illustrates applications of metabolome analysis through the use of case studies.
Introduces readers to the state of the art of omics platforms and all aspects of omics approaches for clinical applications This book presents different high throughput omics platforms used to analyze tissue, plasma, and urine. The reader is introduced to state of the art analytical approaches (sample preparation and instrumentation) related to proteomics, peptidomics, transcriptomics, and metabolomics. In addition, the book highlights innovative approaches using bioinformatics, urine miRNAs, and MALDI tissue imaging in the context of clinical applications. Particular emphasis is put on integration of data generated from these different platforms in order to uncover the molecular landscape of diseases. The relevance of each approach to the clinical setting is explained and future applications for patient monitoring or treatment are discussed. Integration of omics Approaches and Systems Biology for Clinical Applications presents an overview of state of the art omics techniques. These methods are employed in order to obtain the comprehensive molecular profile of biological specimens. In addition, computational tools are used for organizing and integrating these multi-source data towards developing molecular models that reflect the pathophysiology of diseases. Investigation of chronic kidney disease (CKD) and bladder cancer are used as test cases. These represent multi-factorial, highly heterogeneous diseases, and are among the most significant health issues in developed countries with a rapidly aging population. The book presents novel insights on CKD and bladder cancer obtained by omics data integration as an example of the application of systems biology in the clinical setting. Describes a range of state of the art omics analytical platforms Covers all aspects of the systems biology approach—from sample preparation to data integration and bioinformatics analysis Contains specific examples of omics methods applied in the investigation of human diseases (Chronic Kidney Disease, Bladder Cancer) Integration of omics Approaches and Systems Biology for Clinical Applications will appeal to a wide spectrum of scientists including biologists, biotechnologists, biochemists, biophysicists, and bioinformaticians working on the different molecular platforms. It is also an excellent text for students interested in these fields.
Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector Machines presents a new approach to generating text classifiers from examples. The approach combines high performance and efficiency with theoretical understanding and improved robustness. In particular, it is highly effective without greedy heuristic components. The SVM approach is computationally efficient in training and classification, and it comes with a learning theory that can guide real-world applications. Learning To Classify Text Using Support Vector Machines gives a complete and detailed description of the SVM approach to learning text classifiers, including training algorithms, transductive text classification, efficient performance estimation, and a statistical learning model of text classification. In addition, it includes an overview of the field of text classification, making it self-contained even for newcomers to the field. This book gives a concise introduction to SVMs for pattern recognition, and it includes a detailed description of how to formulate text-classification tasks for machine learning.
To comprehend the organizational principle of cellular functions at diff erent levels, an integrative approach with large-scale experiments, the so-called ‘omics’ data including genomics, transcriptomics, proteomics, and metabolomics, is needed. Omics aims at the collective characterization and quantifi cation of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms. Currently, omics is an essential tool to understand the molecular systems that underlie various plant functions. Furthermore, in several plant species, the development of omicsresources has progressed to address the particular biological properties of individual species. Integration of knowledge from omics-based research is an emerging issue as researchers seek to identify significance, gain biological insights and promote translational research. From these perspectives, we intend to provide the emerging aspects of plant systems research based on omics and bioinformatics analyses together with their associated resources and technological advances. Th e present book covers a wide range of omics topics, and discusses the latest trends and application area of plant sciences. In this volume, we have highlighted the working solutions as well as open problems and future challenges in plant omics studies. We believe that this book will initiate and introduce readers to state-of-the-art developments and trends in omics-driven research.