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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

Applying Machine Learning Techniques to Bioinformatics

Price: $340.00 | Publisher: IGI Global

Editors: Umesh Kumar Lilhore, Abhishek Kumar, Sarita Simaiya, Narayan Vyas, Vishal Dutt

Release Date: March 2024 | Copyright: © 2024 | Language: English | Categories: Healthcare, Technology, AI

ISBN: 978-8-3693-1822-5 | DOI: 10.4018/979-8-3693-1822-5

Why are cutting-edge data science techniques such as bioinformatics, few-shot learning, and zero-shot learning underutilized in the world of biological sciences?. In a rapidly advancing field, the failure to harness the full potential of these disciplines limits scientists’ ability to unlock critical insights into biological systems, personalized medicine, and biomarker identification. This untapped potential hinders progress and limits our capacity to tackle complex biological challenges.

The solution to this issue lies within the pages of Applying Machine Learning Techniques to Bioinformatics. This book serves as a powerful resource, offering a comprehensive analysis of how these emerging disciplines can be effectively applied to the realm of biological research. By addressing these challenges and providing in-depth case studies and practical implementations, the book equips researchers, scientists, and curious minds with the knowledge and techniques needed to navigate the ever-changing landscape of bioinformatics and machine learning within the biological sciences.

Designed for academic scholars and practitioners, as well as upper-level undergraduates and graduates seeking to expand their knowledge, this book is a must-read for anyone passionate about the intersection of data science and human biology. Healthcare professionals, biotechnologists, and academics alike will find this resource invaluable for advancing their understanding and capabilities in the dynamic field of bioinformatics.

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  • Chapter 1: Advancing Zero-Shot Learning With Fully Connected Weighted Bipartite Graphs in Machine Learning

    Authors: V. Dankan Gowda, Rama Chaithanya Tanguturi, Neha Patwari, S. B. Sridhara, Sampada Abhijit Dhole

  • Chapter 2: Bioinformatics in Agriculture and Ecology Using Few-Shots Learning From Field to Conservation

    Authors: Jayashri Prashant Shinde, Smitha Nayak, Deepika Amol Ajalkar, Yogesh Kumar Sharma

  • Chapter 3: An Overview and Analysis of Machine Learning Classification Algorithms in Healthcare

    Authors: Soumitra Saha

  • Chapter 4: Ethical and Legal Considerations in Machine Learning: Promoting Responsible Data Use in Bioinformatics

    Authors: Deepika Amol Ajalkar, Yogesh Kumar Sharma, Jayashri Prashant Shinde, Smitha Nayak

  • Chapter 5: A Comprehensive Analysis of the Health Effects of 5G Radiation

    Authors: Soumitra Saha, Shubh Kumar

  • Chapter 6: Bridging Bytes and Biology-Advanced Learning and Bioinformatics in Innovative Drug Discovery

    Authors: Dwijendra Nath Dwivedi, Ghanashyama Mahanty, Varunendra Nath Dwivedi

  • Chapter 7: Challenges and Limitations of Few-Shot and Zero-Shot Learning

    Authors: V. Dankan Gowda, Sajja Suneel, P. Ramesh Naidu, S. V. Ramanan, Sampathirao Suneetha

  • Chapter 8: Unveiling the Potential: A Comprehensive Exploration of Deep Learning and Transfer Learning Techniques in Bioinformatics

    Authors: Umesh Kumar Lilhore, Sarita Simaiya

  • Chapter 9: Unlocking the Future of Healthcare: Biomarkers and Personalized Medicine

    Authors: Samiksha Garse, Divya Dalal, Sneha Dokhale, Shine Devarajan

  • Chapter 10: Unveiling the World of Bioinformatics

    Authors: Khushboo Dhiman, Hardik Dhiman

  • Chapter 11: Ethical Considerations in Sharing Patient Data: A Systematic Review

    Authors: Santhoshkumar, K. Susithra

  • Chapter 12: Exploration of Deep Learning and Transfer Learning in Bioinformatics

    Authors: Yash Mahajan, Muskan Sharma

  • Chapter 13: Exploration of Deep Learning and Transfer Learning Techniques in Bioinformatics

    Authors: Sumit Bansal, Vandana Sindhi, Bhim Sain Singla

  • Chapter 14: Unlocking the Future of Healthcare: Biomarkers and Personalized Medicine

    Authors: Baiju B. V., P. Suresh, G. Subathra, P. Keerthika, Kishor Kumar Sadasivuni, K. Logeswaran

  • Chapter 15: Machine Learning's Potential in Shaping the Future of Bioinformatics Research

    Authors: V. Dankan Gowda, Saptarshi Mukherjee, Sajja Suneel, Dinesh Arora, Ujjwal Kumar Kamila

  • Chapter 16: Exploring Few-Shot Learning Approaches for Bioinformatics Advancements

    Authors: Neha Bhati, Ronak Duggar, Abdullah Alzahrani

  • Chapter 17: Introduction to Bioinformatics and Machine Learning

    Authors: Rakhi Chauhan

  • Chapter 18: Learning From Scarcity: Unlocking Healthcare Insights With Few-Shot Machine Learning

    Authors: Pooja Dixit, Advait Vihan Kommula, Pramod Sing Rathore

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