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· 분류 : 외국도서 > 과학/수학/생태 > 과학 > 생명과학 > 유전학/유전체학
· ISBN : 9781032943411
· 쪽수 : 340쪽
· 출판일 : 2024-12-06
목차
Preface
About the Editors
1. Exploring the Intersection of Metagenomics and Artificial Intelligence
2. Metagenomics and AI: A Synergistic Approach to Data-Driven Insights
3. Techniques for Metagenomic Data Collection and Sequencing
4. Computational Challenges in Metagenomic Data Analysis
5. Machine Learning for Taxonomic Classification of Microbiomes
6. Predictive Modelling of Microbial Communities Using Deep Learning
7. Functional Profiling of Microbial Communities through AI Approaches
8. Enzyme Annotation and Pathway Reconstruction with Machine Learning
9. Metagenomics and Host-Microbiome Interactions in Disease
10. AI-Powered Predictive Modelling for Disease Diagnostics
11. Metagenomic Insights into Ecosystems and Environmental Dynamics
12. AI-Driven Analysis of Environmental Metagenomic Data
13. Constructing and Analysing Microbial Interaction Networks Using AI
14. Integrative Approaches: Combining Metagenomics and Network Science
15. Mining Metagenomic Data for Novel Functional Genes Using AI
16. AI-driven Bioprospecting of Microbial Resources
17. Ethical Issues in AI-Enhanced Metagenomic Research
18. Legal Frameworks for Data Privacy and Ownership in Metagenomics
19. Emerging Trends in Metagenomics and AI Integration
20. AI-Metagenomics Fusion: Paving the Way for Precision Microbiomics
