Artificial Intelligence in Bioinformatics
eBook - ePub

Artificial Intelligence in Bioinformatics

From Omics Analysis to Deep Learning and Network Mining

  1. 268 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Artificial Intelligence in Bioinformatics

From Omics Analysis to Deep Learning and Network Mining

About this book

Artificial Intelligence in Bioinformatics: From Omics Analysis to Deep Learning and Network Mining reviews the main applications of the topic, from omics analysis to deep learning and network mining. The book includes a rigorous introduction on bioinformatics, also reviewing how methods are incorporated in tasks and processes. In addition, it presents methods and theory, including content for emergent fields such as Sentiment Analysis and Network Alignment.  Other sections survey how Artificial Intelligence is exploited in bioinformatics applications, including sequence analysis, structure analysis, functional analysis, protein classification, omics analysis, biomarker discovery, integrative bioinformatics, protein interaction analysis, metabolic networks analysis, and much more. - Bridges the gap between computer science and bioinformatics, combining an introduction to Artificial Intelligence methods with a systematic review of its applications in the life sciences - Brings readers up-to-speed on current trends and methods in a dynamic and growing field - Provides academic teachers with a complete resource, covering fundamental concepts as well as applications

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Yes, you can access Artificial Intelligence in Bioinformatics by Mario Cannataro,Pietro Hiram Guzzi,Giuseppe Agapito,Chiara Zucco,Marianna Milano in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Molecular Biology. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Front Matter
  3. Table of Contents
  4. Copyright
  5. Dedication
  6. Contents
  7. About the authors
  8. Preface
  9. Acknowledgments
  10. List of Illustrations
  11. List of Tables
  12. Introduction
  13. Chapter 1 : Knowledge representation and reasoning
  14. Chapter 2 : Machine learning
  15. Chapter 3 : Artificial intelligence
  16. Chapter 4 : Data science
  17. Chapter 5 : Deep learning
  18. Chapter 6 : Explainability of AI methods
  19. Chapter 7 : Intelligent agents
  20. Introduction
  21. Chapter 8 : Sequence analysis
  22. Chapter 9 : Structure analysis
  23. Chapter 10 : Omics sciences
  24. Chapter 11 : Ontologies in bioinformatics
  25. Chapter 12 : Integrative bioinformatics
  26. Chapter 13 : Biological networks analysis
  27. Chapter 14 : Biological pathway analysis
  28. Chapter 15 : Knowledge extraction from biomedical texts
  29. Chapter 16 : Artificial intelligence in bioinformatics: issues and challenges
  30. Appendix A : Python code examples
  31. Appendix B : Java code examples
  32. Bibliography
  33. Index
  34. A