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The present book “Bioinformatics in Agriculture and Allied Sectors” contains 26 chapters including some fundamental chapters of soil informatics, proteomics, sequence alignment, homology modeling, drug designing and bioinformatics application in aquaculture and avian sectors. Efforts were given to make this book in a simplified way for well understanding and to make very useful for the students, scientists and professionals engaged in research and development of bioinformatics education.
A common approach to understanding the functional repertoire of a genome is through functional genomics. With systems biology burgeoning, bioinformatics has grown to a larger extent for plant genomes where several applications in the form of protein-protein interactions (PPI) are used to predict the function of proteins. With plant genes evolutionarily conserved, the science of bioinformatics in agriculture has caught interest with myriad of applications taken from bench side to in silico studies. A multitude of technologies in the form of gene analysis, biochemical pathways and molecular techniques have been exploited to an extent that they consume less time and have been cost-effective to use. As genomes are being sequenced, there is an increased amount of expression data being generated from time to time matching the need to link the expression profiles and phenotypic variation to the underlying genomic variation. This would allow us to identify candidate genes and understand the molecular basis/phenotypic variation of traits. While many bioinformatics methods like expression and whole genome sequence data of organisms in biological databases have been used in plants, we felt a common reference showcasing the reviews for such analysis is wanting. We envisage that this dearth would be facilitated in the form of this Springer book on Agricultural Bioinformatics. We thank all the authors and the publishers Springer, Germany for providing us an opportunity to review the bioinformatics works that the authors have carried in the recent past and hope the readers would find this book attention grabbing.
With reference to India; contributed articles.
Bioinformatics and Computational Biology: Technological Advancements, Applications and Opportunities is an invaluable resource for general and applied researchers who analyze biological data that is generated, at an unprecedented rate, at the global level. After careful evaluation of the requirements for current trends in bioinformatics and computational biology, it is anticipated that the book will provide an insightful resource to the academic and scientific community. Through a myriad of computational resources, algorithms, and methods, it equips readers with the confidence to both analyze biological data and estimate predictions. The book offers comprehensive coverage of the most essential and emerging topics: Cloud-based monitoring of bioinformatics multivariate data with cloud platforms Machine learning and deep learning in bioinformatics Quantum machine learning for biological applications Integrating machine learning strategies with multiomics to augment prognosis in chronic diseases Biomedical engineering Next generation sequencing techniques and applications Computational systems biology and molecular evolution While other books may touch on some of the same issues and nuances of biological data analysis, they neglect to feature bioinformatics and computational biology exclusively, and as exhaustively. This book's abundance of several subtopics related to almost all of the regulatory activities of biomolecules from where real data is being generated brings an added dimension.
This book provides a comprehensive overview of the concepts and approaches used for sequence, structure, and phylogenetic analysis. Starting with an introduction to the subject and intellectual property protection for bioinformatics, it guides readers through the latest sequencing technologies, sequence analysis, genomic variations, metagenomics, epigenomics, molecular evolution and phylogenetics, structural bioinformatics, protein folding, structure analysis and validation, drug discovery, reverse vaccinology, machine learning, application of R programming in biological data analysis, and the use of Linux in handling large data files.
Knowledge Management is the process by which an organization identifies, creates, manages and delivers information to enhance workforce performance.KM is a discipline that promotes an integrated approach to identifying, capturing, evaluating, retrieving, and sharing all of an enterprise's information assets. These assets may include databases, documents, policies, procedures, and previously un-captured expertise and experience in individual workers. All these issues are covered in thirty three s in the book broadly divided into the following five sections. Fundamentals of Knowledge Management, Latest Tools and Techniques for Knowledge Management, Databases, Data mining, Knowledge Discovery in Biotechnology and Bioinformatics, Data mining and Knowledge Discovery in Agriculture and Allied Fields, Indigenous Knowledge Protection and IPR Issues The book contains original research and case studies by academic and research contributors on strategies, tools, techniques and technologies for Knowledge Management. The focus of this book is on the identification of innovative KM strategies and the application of theoretical concepts to real-world situations. This first serves as a complete introduction to the concepts and principles of KM, starting with basics of data, information, knowledge and wisdom. Clarified differences among Explicit, Implicit and Tacit Knowledge. The book also covers traditional KM approaches as well as emerging topics such as cloud computing, Semantic Web, Rough Computing, Fuzzy logic, Artificial intelligence, Machine learning, social networks, Tools and Techniques for Geo Spatial Data Knowledge Discovery. The focus of the book is on how KM impacts organizations and individuals and steps that should be taken to maximize benefits, including directions for how to select, develop, and evaluate KM systems.
This book, through its overview chapter and 12 country studies, provides useful information on the evolving biotechnological research in Asia, Africa, and Latin America. The emphasis is on the potential biotechnologies hold for agriculture in developing countries. The reports vary in depth of coverage, but all combine to show the urgent need that exists for public- and private-sector investment to ensure that all countries share in the benefits of modern biotechnologies, while minimizing any unintended effects. The book contains a subject index.
This book aims to provide readers with a comprehensive guide to the fundamentals of big data analytics and its applications in various industries and smart societies. What sets this book apart is its in-depth coverage of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems for precision agriculture. The book also delves into the use of big data analytics in healthcare, energy management, and agricultural development, among others. The authors have used clear and concise language, along with relevant examples and case studies, to help readers understand the complex concepts involved in big data analytics. Key Features: Comprehensive coverage of the fundamentals of big data analytics In-depth discussion of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems. Practical examples and case studies to help readers understand complex concepts. Coverage of the use of big data analytics in various industries, including healthcare, energy management, and agriculture Discussion of challenges and legal frameworks involved in big data analytics. Clear and concise language that is easy to understand. This book is a valuable resource for business owners, data analysts, students, and anyone interested in the field of big data analytics. It provides readers with the tools they need to leverage the power of big data and make informed decisions that can help their organizations succeed. Whether you are new to the field or an experienced practitioner, "Demystifying Big Data Analytics for Industries and Smart Societies" is must-read.
Microbes are ubiquitous in nature, and plant-microbe interactions are a key strategy for colonizing diverse habitats. The plant microbiome (epiphytic, endophytic and rhizospheric) plays an important role in plant growth and development and soil health. Further, rhizospheric soil is a valuable natural resource, hosting hotspots of microbes, and is vital in the maintenance of global nutrient balance and ecosystem function. The term endophytic microbes refers to those microorganisms that colonize the interior the plants. The phyllosphere is a common niche for synergism between microbes and plants and includes the leaf surface. The diverse group of microbes are key components of soil-plant systems, and where they are engaged in an extensive network of interactions in the rhizosphere/endophytic/phyllospheric they have emerged as an important and promising tool for sustainable agriculture. Plant microbiomes help to directly or indirectly promote plant growth using plant growth promoting attributes, and could potentially be used as biofertilizers/bioinoculants in place of chemical fertilizers. This book allows readers to gain an understanding of microbial diversity associated with plant systems and their role in plant growth, and soil health. Offering an overview of the state of the art in plant microbiomes and their potential biotechnological applications in agriculture and allied sectors, it is a valuable resource for scientists, researchers and students in the field of microbiology, biotechnology, agriculture, molecular biology, environmental biology and related subjects.