AI-Driven Plant Science: Advancing Crop Performance Through Omics Integration and Physiology
Editat de Osamah Shihab Albahrey, Jameel R. Al-Obaidien Limba Engleză Paperback – feb 2027
- Integrates AI concepts with real-world case studies and actionable insights
- Presents a broad and comprehensive exploration of AI application in plant science and crop breeding
- Leverages emerging technologies in an applied approach
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Specificații
ISBN-13: 9780443451607
ISBN-10: 0443451605
Pagini: 285
Dimensiuni: 152 x 229 mm
Editura: ELSEVIER SCIENCE
ISBN-10: 0443451605
Pagini: 285
Dimensiuni: 152 x 229 mm
Editura: ELSEVIER SCIENCE
Cuprins
Part 1: Foundations of AI in Plant Omics
1. The Future of Agriculture: AI Meets Plant Sciences
2. AI Fundamentals for Plant Research: Concepts and Applications
3. AI-Driven Systems Biology: Connecting Data for Plant Research
Part 2: Genomics, Breeding, and Epigenetics
4. Decoding Plant Genomes: AI in Sequencing and Annotation
5. AI-Assisted Breeding for Climate-Resilient Crops
6. Epigenetics and AI: Unlocking Gene Regulation in Plants
Part 3: Transcriptomics, Proteomics, and Metabolomics
7. Deep Learning in Plant Transcriptomics: Understanding Gene Expression Dynamics
8. AI in Plant Stress Biology: Predicting Adaptive Responses to Abiotic Stress
9. AI in Plant Proteomics: Mapping Protein Functions and Interactions
10. Metabolomics and AI: Pathways to Discovery
11. AI in Plant Pathology: Disease Resistance, Pest Control, and Weed Management
12. High-Throughput Phenotyping: AI in Action
13. AI for Sustainable Agriculture
Part 4: Future Directions and Ethical Considerations
14. Synthetic Biology and AI: Shaping the Future of Plant Biotechnology
15. Ethical, Regulatory, and Data Security Challenges in AI-Driven Plant Research
1. The Future of Agriculture: AI Meets Plant Sciences
2. AI Fundamentals for Plant Research: Concepts and Applications
3. AI-Driven Systems Biology: Connecting Data for Plant Research
Part 2: Genomics, Breeding, and Epigenetics
4. Decoding Plant Genomes: AI in Sequencing and Annotation
5. AI-Assisted Breeding for Climate-Resilient Crops
6. Epigenetics and AI: Unlocking Gene Regulation in Plants
Part 3: Transcriptomics, Proteomics, and Metabolomics
7. Deep Learning in Plant Transcriptomics: Understanding Gene Expression Dynamics
8. AI in Plant Stress Biology: Predicting Adaptive Responses to Abiotic Stress
9. AI in Plant Proteomics: Mapping Protein Functions and Interactions
10. Metabolomics and AI: Pathways to Discovery
11. AI in Plant Pathology: Disease Resistance, Pest Control, and Weed Management
12. High-Throughput Phenotyping: AI in Action
13. AI for Sustainable Agriculture
Part 4: Future Directions and Ethical Considerations
14. Synthetic Biology and AI: Shaping the Future of Plant Biotechnology
15. Ethical, Regulatory, and Data Security Challenges in AI-Driven Plant Research