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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.
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.
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.
This book provides an up-to-date review of classic and advanced bioinformatics approaches and their utility in rice research. It summarizes databases and tools for analyzing DNA, proteins and gene expression profiles, mapping genetic variations, annotation of protein and RNA molecules, phylogenetic analysis, and pathway enrichment. In addition, it presents high-throughput technologies that are widely used to provide deep insights into the genetic architecture of important traits in the rice genome. The book subsequently discusses techniques for identifying RNA-protein, DNA-protein interactions, and molecular markers, including SNP and microsatellites, in the contexts of rice breeding and genetics. Lastly, it explores various tools that are used to identify and characterize non-coding RNA in rice and their potential role in rice research.
This book: (i) introduces fundamental and applied bioinformatics research in the field of plant life sciences; (ii) enlightens the potential users towards the recent advances in the development and application of novel computational methods available for the analysis and integration of plant -omics data; (iii) highlights relevant databases, softwares, tools and web resources developed till date to make ease of access for researchers working to decipher plant responses towards stresses; and (iv) presents a critical cross-talks on the available high-throughput data in plant research. Therefore, in addition to being a reference for the professional researchers, it is also of great interest to students and their professors. Considering immense significance of plants for all lives on Earth, the major focus of research in plant biology has been to: (a) select plants that best fit the purposes of human, (b) develop crop plants superior in quality, quantity and farming practices when compared to natural (wild) plants, and (c) explore strategies to help plants to adapt biotic and abiotic/environmental stress factors. Accordingly the development of novel techniques and their applications have increased significantly in recent years. In particular, large amount of biological data have emerged from multi-omics approaches aimed at addressing numerous aspects of the plant systems under biotic or abiotic stresses. However, even though the field is evolving at a rapid pace, information on the cross-talks and/or critical digestion of research outcomes in the context of plant bioinformatics is scarce. “Plant Bioinformatics: Decoding the Phyta” is aimed to bridge this gap.
This textbook introduces fundamental concepts of bioinformatics and computational biology to the students and researchers in biology, medicine, veterinary science, agriculture, and bioengineering . The respective chapters provide detailed information on biological databases, sequence alignment, molecular evolution, next-generation sequencing, systems biology, and statistical computing using R. The book also presents a case-based discussion on clinical, veterinary, agricultural bioinformatics, and computational bioengineering for application-based learning in the respective fields. Further, it offers readers guidance on reconstructing and analysing biological networks and highlights computational methods used in systems medicine and genome-wide association mapping of diseases. Given its scope, this textbook offers an essential introductory book on bioinformatics and computational biology for undergraduate and graduate students in the life sciences, botany, zoology, physiology, biotechnology, bioinformatics, and genomic science as well as systems biology, bioengineering and the agricultural, and veterinary sciences.
This title includes a number of Open Access chapters. Climate change will severely impact the world’s food supply unless steps are taken to increase crop resilience. Otherwise, the negative effects on both the yield and the quality of crop plants are predicted to be immense. Plant genomics is a potentially powerful defense against this looming threat. This compendium volume offers a global perspective on the topic, with contributions from 42 eminent researchers from 12 nations around the world. The editor is a respected and published scientist in the bioinformatics field, who has chosen articles in the following topics: An overview of the genetic challenges presented by climate change A genomic toolkit for crop-related research Specific methods of improvement for specific crop by means of genomic applications The hand-picked up-to-date research makes this volume an excellent reference not only for university-level academics, but also for policymakers and stakeholders who must tackle the challenge of the world’s food security.
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.
The sequencing of genomes has been completed for an increasing number of crop species, and researchers have now succeeded in isolating and characterising many important QTLs/genes. High expectations from genomics, however, are waving back toward the recognition that crop physiology is also important for realistic improvement of crop productivity. Complex processes and networks along various hierarchical levels of crop growth and development can be thoroughly understood with the help of their mathematical description – modelling. The further practical application of these understandings also requires quantitative predictions. In order to better support design, engineering and breeding for new crops and cultivars for improving agricultural production under global warming and climate change, there is an increasing call for an interdisciplinary research approach, which combines modern genetics and genomics, traditional physiology and biochemistry, and advanced bioinformatics and modelling. Such an interdisciplinary approach has been practised in various research groups for many years. However, it does not seem to be fully covered in the format of book publications. We want to initiate a book project on crop systems biology - narrowing the gaps between genotypes and phenotypes and the gaps between crop modelling and genetics/genomics, for publication in 2013/2014. The book will be meant for those scientists and graduate students from fundamental plant biology and applied crop science who are interested in bridging the gap between these two fields. We have invited a group of scientists (who have very good track records in publishing excellent papers in this field or in a closely related area) to contribute chapters to this new book, and they have agreed to do so.​