Data science for genomics. (2022)

• Record Type: Book
• Further Information: Note: Edited by Amit Kumar Tyagi, Ajith Abraham.
• Editors: Tyagi, Amit Kumar, 1988-; Abraham, Ajith, 1968-
• Contents: 1. Introduction to Data Science; 2. Toolboxes for Data Scientists; 3. Machine Learning and Deep Learning: A Concise Overview; 4. Artificial Intelligence; 5. Data Privacy and Data Trust; 6. Visual Data Analysis and Complex Data Analysis; 7. Big Data programming with Apache Spark and Hadoop; 8. Information Retrieval and Recommender Systems; 9. Statistical Natural Language Processing for Sentiment Analysis; 10. Parallel Computing and High-Performance Computing; 11. Data Science, Genomics, Genomes, and Genetics; 12. Blockchain Technology for securing Genomic data; 13. Cloud, edge, fog, etc., for communicating and storing data for Genome; 14. Open Issues, Challenges and Future Research Directions towards Data science and Genomics; 15. Privacy Laws; 16. Ethical Concerns; 17. Self-study questions; 18. Problem-based learning; 19. Key Terms/ Glossary; 20. Appendix – Keeping up to Date; 21. Bibliography
• Publisher Details: Amsterdam : Academic Press
• Publication Date: 2022
• Extent: 1 online resource
• Subjects: 572.86028557; Genomics -- Data processing
• Languages: English
• ISBNs: 9780323985765
• Related ISBNs: 9780323983525
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.