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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.

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Applying Machine Learning Techniques to Bioinformatics: Few-Shot and Zero-Shot Methods

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 Deadline15 November 2023
Abstract Acceptance Notification15 December 2023
Full Chapter Submission Deadline15 January 2024
Chapter Acceptance Notification15 February 2024
Projected Book Release DateApril 2024
Important Guidelines
Citation StyleAPA (7th Edition)
Formatting11 pt Times Roman, 1.5 line spacing
OriginalityPlagiarism Under 10%, 0% AI Generated Content
Headings
  • Heading 1: ALL BOLD CAPS
  • Heading 2: Bold Title Case
  • Heading 3: Bold Italic Title Case
  • Heading 4: Bold Italic Sentence case
  • Heading 5: Light Italic Sentence case
  • Paragraphs: Should be Numbered (1.1, 1.1.1, etc.)
Chapter submissions are closed. Thank you for your cooperation.
  • 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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