Bioinformatics In Agriculture

Bioinformatics in Agriculture: Next Generation Sequencing Era is a comprehensive volume presenting an integrated research and development approach to the practical application of genomics to improve agricultural crops. Exploring both the theoretical and applied aspects of computational biology, and focusing on the innovation processes, the book highlights the increased productivity of a translational approach. Presented in four sections and including insights from experts from around the world, the book includes: Section I: Bioinformatics and Next Generation Sequencing Technologies; Section II: Omics Application; Section III: Data mining and Markers Discovery; Section IV: Artificial Intelligence and Agribots. Bioinformatics in Agriculture: Next Generation Sequencing Era explores deep sequencing, NGS, genomic, transcriptome analysis and multiplexing, highlighting practices forreducing time, cost, and effort for the analysis of gene as they are pooled, and sequenced. Readers will gain real-world information on computational biology, genomics, applied data mining, machine learning, and artificial intelligence. This book serves as a complete package for advanced undergraduate students, researchers, and scientists with an interest in bioinformatics. Discusses integral aspects of molecular biology and pivotal tool sfor molecular breeding Enables breeders to design cost-effective and efficient breeding strategies Provides examples ofinnovative genome-wide marker (SSR, SNP) discovery Explores both the theoretical and practical aspects of computational biology with focus on innovation processes Covers recent trends of bioinformatics and different tools and techniques

This book illustrates the importance and significance of bioinformatics in the field of agriculture. It first introduces the basic concepts of bioinformatics, such as homologous sequence and gene function analyses, determination of protein structures, and discusses machine learning applications for an in-depth understanding of the desired genes and proteins based on commonly used bioinformatics software and tools, e.g. BLAST, molecular modelling, molecular-docking and simulations, protein-protein and domain-domain interactions. The book also describes recent advances in the high-throughput analysis of whole genome and transcriptome using next-generation sequencing platforms, and functional proteome studies. It also examines the role of computational biology in understanding and improving the nutrient quality and yield of crops. Lastly, the book explores a comprehensive list of applications of bioinformatics to improve plant yield, biomass, and health, and the challenges involved.

Advances in information technology and next generation sequencing have propelled the use of bioinformatics in agriculture, especially in the area of crop improvement. An extremely large amount of genomics data is available from plants and animals due to tremendous improvements in the field. This book acquaints readers with state-of-the-art sequencing technologies, recent developments in computing algorithms, and certain biological perspectives that influence development of bioinformatics tools by giving specific examples from model plant species. The challenge is now to make sense and use of this wealth of data.

Biotechnological tools supplement various conventional approaches in conservation, characterization and utilization for increasing production and productivity of agricultural and horticultural crops. The emerging field of bioinformatics is an integrated field arising from merging of biology and informatics. It is a conglomeration of various new frontiers of science like genomics, proteomics, metabolomics etc. The rich warehouse of proteome and genome information nearly doubling every year has significant implications and applications in various areas of science including agriculture, horticulture, forestry and food science. Cheminformatics is specialized to a range of problems in the field of chemistry. Chemical pesticide reduction is possible by adopting cheminformatics methods to identify naturally occurring chemical compounds in crops which act against pests. Bioinformatics has transformed the discipline of life science from a purely lab based science to an information science as well. The ICAR has recently launched a National Agricultural Bioinformatics Grid (NABG) to serve as a computational facility in developing national biodatabases and data warehouses. The present book Agriculture Bioinformatics is a compilation of 17 information packed s authored by working scientists in the respective discipline. In addition to the theoretical information, practical and applied aspects to boost productivity and quality of crops are given.

The book deals with various tools and applications of bioinformatics in the fields of: o agriculture, corals, structural bioinformatics, data-mining, text-mining; o medicinal plants, antibiotics, protein structure prediction, drug design; o gene expression, micro-arrays, proteomics, molecular phylogenic location of the Indian Liver Fluke, rough sets to predict protein structural class; o artificial neural networks for prediction of amino acids levels, plant systems biology, molecular modeling, homology modeling, bio-efficacy of indigenous bacillus through in-silico approach; o fresh aquaculture and fisheries, pesticides and insecticides, databases and tools development in the relevant area. The book would be of much use to the person working in the field of agricultural biotechnology, bioinformatics, computer science and applied statistics. This can act as a book for M.Sc, M.Tech and Ph.D students of and the faculty of Bioinformatics/Biotechnologists.

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.

Bioinformatics is an integrative field of computer science, genetics, genomics, proteomics, and statistics, which has undoubtedly revolutionized the study of biology and medicine in past decades. It mainly assists in modeling, predicting and interpreting large multidimensional biological data by utilizing advanced computational methods. Despite its enormous potential, bioinformatics is not widely integrated into the academic curriculum as most life science students and researchers are still not equipped with the necessary knowledge to take advantage of this powerful tool. Hence, the primary purpose of our book is to supplement this unmet need by providing an easily accessible platform for students and researchers starting their career in life sciences. This book aims to avoid sophisticated computational algorithms and programming. Instead, it will mostly focus on simple DIY analysis and interpretation of biological data with personal computers. Our belief is that once the beginners acquire these basic skillsets, they will be able to handle most of the bioinformatics tools for their research work and to better understand their experimental outcomes. The third volume is titled In Silico Life Sciences: Agriculture. It focuses on plant genetic, genomic, transcriptomic, proteomic and metabolomics data. Using examples of new crop diseases-emergence, crop productivity and biotic/abiotic stress tolerance, this book illustrates how bioinformatics can be an integral components of modern day plant science research.