Main description:

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.

Contents:

PART 1 ARTIFICIAL INTELLIGENCE: METHODS 1. Knowledge Representation and Reasoning 2. Machine Learning 3. Artificial Intelligence 4. Data Science 5. Deep Learning 6. Explainability of AI methods 7. Intelligent Agents

PART 2 ARTIFICIAL INTELLIGENCE: BIOINFORMATICS 8. Sequence Analysis 9. Structure Analysis 10. Omics Sciences 11. Ontologies in Bioinformatics 12. Integrative Bioinformatics 13. Biological Networks Analysis 14. Biological Pathway Analysis 15. Knowledge Extraction from Biomedical Texts 16. Artificial Intelligence in Bioinformatics: Issues and Challenges