Genomic Intelligence
eBook - ePub

Genomic Intelligence

Metagenomics and Artificial Intelligence

  1. 340 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Genomic Intelligence

Metagenomics and Artificial Intelligence

About this book

The field of metagenomics has revolutionized our comprehension of microbial diversity and function across various habitats, from the human body to terrestrial and aquatic environments. Simultaneously, advancements in AI have empowered researchers to analyze vast troves of genomic data with unprecedented speed and precision, facilitating new insights into the complex interplay between microorganisms and their surroundings.

The subject matter in this book provides an overview of metagenomics and discusses the combination of metagenomics and AI and its significant consequences for advancements in science. The chapters examine the approaches, difficulties, and revolutionary uses of AI in metagenomics and provide insight into the convergence of genomics, metagenomics, and AI's potential to revolutionize diverse fields from healthcare to environmental.

Print edition not for sale in India.

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Yes, you can access Genomic Intelligence by Sheetanshu Gupta,Dhirendra Kumar,Radhika Negi,Ranjan Singh,Mohammad Javed Ansari,Shakuli Kashyap,Sudhir Mehrotra in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Genetics & Genomics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
CRC Press
Year
2024
eBook ISBN
9781040269572
Edition
0
Topic
Biological Sciences
Subtopic
Genetics & Genomics
Index
Biological Sciences

Table of contents

  1. Cover Page
  2. Half Title page
  3. Title Page
  4. Copyright Page
  5. Contents
  6. Preface
  7. About the Editors
  8. 1 Exploring the Intersection of Metagenomics and Artificial Intelligence
  9. 2 Metagenomics and AI: A Synergistic Approach to Data-Driven Insights
  10. 3 Techniques for Metagenomic Data Collection and Sequencing
  11. 4 Computational Challenges in Metagenomic Data Analysis
  12. 5 Machine Learning for Taxonomic Classification of Microbiomes
  13. 6 Predictive Modeling of Microbial Communities Using Deep Learning
  14. 7 Functional Profiling of Microbial Communities through AI Approaches
  15. 8 Enzyme Annotation and Pathway Reconstruction with Machine Learning
  16. 9 Metagenomics and Host-Microbiome Interactions in Disease
  17. 10 AI-Powered Predictive Modelling for Disease Diagnostics
  18. 11 Metagenomic Insights into Ecosystems and Environmental Dynamics
  19. 12 AI-driven Analysis of Environmental Metagenomic Data
  20. 13 Constructing and Analysing Microbial Interaction Networks using AI
  21. 14 Integrative Approaches: Combining Metagenomics and Network Science
  22. 15 Mining Metagenomic Data for Novel Functional Genes Using AI
  23. 16 AI-Driven Bioprospecting of Microbial Resources
  24. 17 Ethical Issues in AI-Enhanced Metagenomic Research
  25. 18 Legal Frameworks for Data Privacy and Ownership in Metagenomics
  26. 19 Emerging Trends in Metagenomics and AI Integration
  27. 20 AI-Metagenomics Fusion: Paving the Way for Precision Microbiomics