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Data Science for Genomics

Data Science for Genomics


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About the Book

Data Science for Genomics

Table of 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

About the Author :
Amit Kumar Tyagi is an Assistant Professor at the National Forensic Sciences University, Gandhinagar, India. He previously held academic and research positions, including at Vellore Institute of Technology (2019–2022), and earned his PhD from Pondicherry Central University in 2018. He has supervised doctoral and master’s students and contributed to research projects on privacy and security in vehicular applications and medical cyber-physical systems. He has published over 200 peer-reviewed papers and holds more than 25 patents in areas such as deep learning, the Internet of Things, cyber-physical systems, and computer vision. He has edited over 25 books and authored four books in related fields, and has received multiple research awards. His interests include machine-based communications, blockchain, and secure, privacy-preserving computing. He is a member of ACM and IEEE. Dr. Ajith Abraham is the Pro Vice-Chancellor for Academics, Research, Incubation, and International Relations at Bennette University. He is also the Founding Director of Machine Intelligence Research Labs (MIR Labs), a global non-profit scientific network that connects academia and industry to support research and innovation. He is also serving as Vice Chancellor of Sai University, Chennai. His research interests include artificial intelligence and machine intelligence, cyber-physical systems, the Internet of Things (IoT), network security, Web intelligence, sensor networks, and data mining. He serves as Chair of the IEEE Systems, Man, and Cybernetics Society Technical Committee on Soft Computing and has held editorial leadership roles, including Editor-in-Chief of Engineering Applications of Artificial Intelligence. Dr. Abraham earned his Ph.D. in Computer Science from Monash University, Australia.


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Product Details
  • ISBN-13: 9780323983525
  • Publisher: Elsevier Science & Technology
  • Publisher Imprint: Academic Press Inc
  • Height: 276 mm
  • No of Pages: 312
  • Width: 216 mm
  • ISBN-10: 0323983529
  • Publisher Date: 02 Dec 2022
  • Binding: Paperback
  • Language: English
  • Weight: 784 gr


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