Description
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
Table of Contents
1. Advances in Agricultural Bioinformatics: Outlook of Multi-Omics Approaches2. Promises and Benefits of Omic approaches to Data driven science industries3. Bioinformatics intervention in functional genomics: current status and future perspective – An overview4. Genome informatics: Present status and Future Prospects in agriculture5. Genomics and its applications for crop improvement why not here crop specific like cotton, musrard, wheat6. Genome-wide Predictions, Structural and Functional Annotations of Plant Transcription Factor Gene Families: A Bioinformatics Approach7. Proteomics and their applications to understand the biology of agricultural crops8. Metabolomics and Sustainable Agriculture: Concepts, Applications and Perspectives9. Plant Metabolomics: A New Era in the Advancement of Agricultural Research10. Exploring NGS-based RNA-Seq Transcriptomes of Crops Responding to Abiotic Stress11. Identification of novel RNAs in plants with the help of Next Generation Sequencing Technologies12. Molecular Evolution, Three Dimensional Structural Characteristics, Mechanism of Action and Functions of Plant Beta-galactosidases13. Next generation genomics: toward decoding domestication history of crops14. In-silico identification of Small RNAs, a tiny silent tool against agriculture pest15. Bioinformatics-assisted multi-omics approaches to improve the agronomic traits in cotton16. Omics-assisted Understanding of BPH Resistance in Rice: Current Updates and Future Prospective 17. Contemporary Genomic Approaches in Modern Agriculture for Improving Tomato Varieties18. Characterization of drought tolerance in maize Omics approaches19. Deciphering the genomic hotspots in wheat for key breeding traits using comparative and structural genomics20. Prospects of molecular markers for wheat improvement in post genomic era21. Omics Approaches for Biotic, Abiotic and Quality Traits Improvement in Potato (Solanum tuberosum L.)22. Tea plant genome sequencing: prospect for crop improvement through genomics tools23. Next Generation Sequencing and Viroid Research24. Computational analysis for plants Virus identification Using Next Generation Sequencing25. Microbial degradation of herbicides in contaminated soils by following computational approaches26. Chloroplast genome and Plant-Virus Interaction27. Deciphering soil microbiota using metagenomic approach for sustainable agriculture: An overview28. Concepts and Applications of Bioinformatics for Sustainable Agriculture29. Application of high throughput structural and functional genomic technologies in crop nutrition research30. Bioinformatics approach for whole transcriptomics-based marker prediction in agriculture crops31. Computational approaches towards SNP discovery and its applications in plant breeding32. Bioinformatics intervention in identification and development of molecular markers: An Overview33. Deciphering comparative and structural variation that regulates abiotic stress response34. Deep Learning Applied to Computational Biology and Agricultural Sciences35. Image processing based artificial intelligence system for rapid detection of plant diseases36. Uses and Applications of Artificial intelligence and Big Data in agriculture: Smart Farming37. Artificial Intelligence: The future of Agricultural Sciences
