Narayan Vyas, an academician at Vivekananda Global University, specializes in computer science, focusing on IoT and Mobile App Development. He has trained over 1000 students globally and published extensively in Scopus journals. An active IEEE member, his research interests include Remote Sensing, Machine Learning, and Computer Vision.
Applying Machine Learning Techniques to Bioinformatics: Few-Shot and Zero-Shot Methods
Publisher: IGI Global
Editors: Umesh Kumar Lilhore, Abhishek Kumar, Sarita Simaiya, Narayan Vyas, Vishal Dutt
This book provides an in-depth look at how cutting-edge data science methods might be applied to biological studies. We explore how bioinformatics, few-shot learning, and zero-shot learning interact with one another, and how this dynamic has had a significant effect on our knowledge of biological systems, customized medicine, and biomarker identification. Our goal is to provide a comprehensive analysis of these emerging disciplines.
| Important Dates | |
|---|---|
| Abstract Submission Deadline | 15 November 2023 |
| Abstract Acceptance Notification | 15 December 2023 |
| Full Chapter Submission Deadline | 15 January 2024 |
| Chapter Acceptance Notification | 15 February 2024 |
| Projected Book Release Date | April 2024 |
| Important Guidelines | |
|---|---|
| Citation Style | APA (7th Edition) |
| Formatting | 11 pt Times Roman, 1.5 line spacing |
| Originality | Plagiarism Under 10%, 0% AI Generated Content |
| Headings |
|
Chapter 1: Introduction to Bioinformatics and Machine Learning
Chapter 2: Overview of Bioinformatics and its potential applications
Chapter 3: Few-Shot Learning and Zero-Shot Learning Paradigms
Chapter 4: Unlocking the Future of Healthcare - Biomarkers and Personalized Medicine
Chapter 5: From Fields to Conservation - Bioinformatics in Agriculture and Ecology
Chapter 6: Few-Shot Learning Techniques for Bioinformatics
Chapter 7: Zero-Shot Learning Techniques in Biological Contexts
Chapter 8: AI-Driven Drug Discovery - Pioneering Bioinformatics and Advanced Learning
Chapter 9: Exploration of Deep Learning & Transfer Learning techniques in Bioinformatics
Chapter 10: Integration of Domain-Specific Knowledge
Chapter 11: Evaluating and Benchmarking Few-Shot and Zero-Shot Models
Chapter 12: Guidelines & Ethical Consideration for Responsible Use of AI in Bioinformatics
Chapter 13: Future Directions and Emerging Trends
Chapter 14: Case Studies on Few-Shot and Zero-Shot Learning in Bioinformatics
Chapter 15: Limitations and Future Research Scope in Bioinformatics
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