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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.
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
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