Sustainable Quantum Bioinformatics

Raghavendra M. Devadas, PhD is an Assistant Professor at the Manipal Institute of Technology at the Manipal Academy of Higher Education, Bengaluru, Karnataka, India. He has published two books, filed two patents, and received two grants. His areas of interest include machine learning, software engineering, fuzzy logic, and databases.Preethi, PhD is an Assistant Professor in the Department of Information Technology at the Manipal Institute of Technology with more than 17 years of teaching experience. She has more than 35 publications in international journals and conferences of repute. Her research interests include computer architecture, IoT, cybersecurity, and image processing.Praveen Gujjar, PhD is an Associate Professor and Area Head of Business Analytics in the CMS Business School at Jain University with more than 16 years of teaching experience. He has authored numerous publications in reputed journals, holds 86 patents, and has secured major research grants from multiple entities. He specializes in data visualization, predictive analytics, and prescriptive analytics.Sowmya T., PhD is an Assistant Professor at the Manipal Institute of Technology. She received her Ph.D. from Christ University in Bengaluru. Her current research interests include network security.Yashaswini K.A., PhD is an experienced academician with more than 16 years of teaching experience in Computer Science and Engineering. She serves as an Assistant Professor at the Manipal Institute of Technology in Bengaluru under the Manipal Academy of Higher Education. Her areas of expertise include artificial intelligence, machine learning, and data analytics.Bharti Jagwani Motwani, PhD is an Academic Director of the Online Master of Science and Business Analytics and a Clinical Associate Professor in the Robert Smith College of Business at the University of Maryland. She is the sole author of many books related to machine learning and artificial intelligence. Her research focuses on machine and deep learning.

• Preface xxi1 Eco-Qubit Architectures: Energy-Optimized Quantum-Classical Hybrid Algorithms for Low-Carbon Genomic Variant Analysis 1Kiran Siripuri, Rajanikanth Aluvalu and Mallellu Sai Prashanth1.1 Introduction 21.2 Background and Motivation 31.3 Framework Overview: Eco-Qubit Architectures 51.4 Core Innovations and Techniques 71.5 Benchmarking and Results 101.6 Carbon Footprint Index (CFI): Environmental Metrics 121.7 Case Study: Eco-Qubit Variant Calling in Practice 141.8 Future Directions and Discussion 161.9 Conclusion 191.10 Acknowledgements 192 The Quantum Leap in Bioinformatics: Rethinking Biological Computation Beyond Classical Limits 21Sanjeev Prakashrao Kaulgud, Abhinandan Shirahatti, Mrutyunjaya M. S., Madhusudhan M. V. and Afroz Pasha2.1 Introduction 222.2 Limitations of Classical Bioinformatics 232.3 Basics of Quantum Computing for Bioinformatics 252.4 Applications of Quantum Computing in Bioinformatics 272.5 Challenges and Limitations of Quantum Bioinformatics 292.6 Future Directions and Opportunities in Quantum2.7 Integrating Sustainability Into Quantum Bioinformatics 332.8 Case Study-1: Quantum Protein Folding with Minimal Energy Footprint 352.9 Case Study-2: Quantum-Assisted Drug Discovery Using Variation Quantum Eigensolver (VQE) 372.10 Conclusion 393 Green Algorithms for Biomedical Data Processing: Towards Sustainable Quantum Bioinformatics 43Usha Rani R.E.3.1 Introduction 443.2 Background Concepts 453.3 Green Algorithms: Concepts and Metrics 513.4 Quantum Algorithms for Biomedical Data 543.5 Case Studies and Applications 573.6 Challenges 613.7 Roadmap to Sustainable and Scalable Quantum Bioinformatics 633.8 Conclusion 694 Quantum Machine Learning in Systems Biology 73Sanjeev Prakashrao Kaulgud, Prabhuraj Metipatil, Vishwanath Hulipalled, Siddanagouda Somanagouda Patil and Sonia Maria Dsouza4.1 Introduction 744.2 Fundamentals of Quantum Machine Learning 784.3 Role of Quantum Machine Learning in Systems Biology 844.4 Case Study 1: Quantum Machine Learning for Cancer Subtype Classification 894.5 Case Study 2: Quantum Neural Networks for Protein Structure Prediction 914.6 Conclusion 935 Quantum-Guided Distillation of Biomedical Transformers: A Green Hybrid Framework for Sustainable Clinical NLP 97Karthik B. U., Mrutyunjaya M. S. and Vishwanath Desai5.1 Introduction 985.2 Literature Survey 1005.3 Proposed Method 1025.4 Results and Discussion 1135.5 Conclusion and Future Work 1216 Quantum Secure Healthcare Data: A Comprehensive Analysis of Emerging Threats and Advanced Protection Technologies 125Johan Daniel M., Naresh Rathod and Tintu Vijayan6.1 The Current Landscape of Healthcare Data Security 1266.2 Emerging Security Technologies 1286.3 AI Ethics and Bias Mitigation 1336.4 Current Threat Landscape: 2025 Security Developments 1346.5 Ransomware Pandemic in Healthcare: The 2025 Crisis Unprecedented Attack Escalation 1356.6 Precision Medicine and Genomic Data Security 1366.7 5G Networks and Healthcare Security Architecture 1386.8 Supply Chain Security Crisis of Medical Devices 1396.9 Regulatory Development Process and Compliance Diction 1406.11 Health Information Exchange Vulnerabilities 1436.12 Advanced Threat Intelligence and Detection Systems 1446.13 Emerging Technologies and Future Security Paradigms 1456.14 Regulatory Evolution and Global Governance 1466.15 Conclusion 1477 Energy-Optimized Quantum State Encoding Methodologies for High-Dimensional, Heterogeneous Biological Big Data 151Pavithra G., Ashwini S.S., Hamsaveni M. and Salma Itagi7.1 Introduction 1527.2 Characteristics of Biological Big Data and Energy Constraints 1547.3 Mathematical Intuition of Quantum Encoding Schemes 1557.4 Comparative Energy Analysis: Classical vs. Quantum Approaches 1597.5 Case Studies in Biological Big Data 1627.6 Methods and Experimental Section 1637.7 Challenges and Open Problems 1667.8 Future Directions 1677.9 Conclusion 1678 Green Quantum Computing Approaches in Bioinformatics and Precision Medicine 171Nikitha K. and Renushree S.8.1 Introduction 1728.2 Environmental Challenges in Classical Bioinformatics 1748.3 Foundations of Green Quantum Computing 1788.4 Green Quantum Architectures for Bioinformatics 1818.5 Applications in Precision Medicine 1868.6 Ethical, Policy, and Sustainability Considerations 1878.7 Challenges and Implementation Barriers 1898.8 Future Research Directions 1918.9 Conclusion 1939 Quantum-Enhanced Bioinformatics for Early Disease Detection and Personalized Treatment Planning 197Nikitha K. and Renushree S.9.1 Introduction 1989.2 Classical Bioinformatics 2019.3 Quantum-Enhanced Bioinformatics Framework 2049.4 Applications in Early Disease Diagnosis 2109.5 Quantum-Enabled Personalized Medicine 2139.6 Sustainability and Responsible Innovation 2169.7 Implementation Challenges 2189.8 Future Research Directions 2209.9 Conclusion 22310 Blueprint for a Sustainable Quantum Bioinformatics Ecosystem 227Sanjeev Prakashrao Kaulgud, Mrutyunjaya M.S., Sonia Maria D'Souza, Prabhuraj Metipatil, Vishwanath Hulipalled and Siddanagouda Somanagouda Patil10.1 Introduction 22810.2 Foundations of Quantum Bioinformatics 23010.3 Sustainability Principles in Quantum Bioinformatics 23210.4 Architecture of a Sustainable Quantum Bioinformatics Ecosystem 23510.5 Quantum Algorithms and Computational Workflows 23710.6 Data Management, Security, and Ethical Governance 23910.7 Applications and Case Studies in Sustainable Life Sciences 24110.8 Challenges, Workforce Development, and Policy Considerations 24310.9 Policy, Regulation, and Risk Mitigation Strategies 24510.10 Future Roadmap 24610.11 Conclusion 24711 Quantum-Enhanced Protein Folding and Drug Discovery with Energy-Aware Algorithms 251Nikitha K., Renushree S. and Ajithkumar M.11.1 Introduction 25211.2 Fundamentals of Protein Folding and Drug Discovery 25911.3 Quantum Computing Foundations for Biomolecular Problems 26211.4 Quantum Algorithms for Protein Folding 26511.5 Quantum-Enhanced Drug Discovery Pipelines 26911.6 Energy-Aware Quantum Algorithms 27111.7 Sustainability Implications in Drug Discovery 27411.8 Case Studies and Experimental Implementations 27611.9 Challenges and Open Research Issues 27811.10 Future Research Directions 27911.11 Conclusion 28112 Ethics, Equity, and Ecological Intelligence in Quantum Bioinformatics: A Theoretical Framework for Responsible Life Science Innovation 285Anubhab Parashar, Tintu Vijayan and Jayanthi Kamalasekaran12.1 Introduction 28612.2 Conceptual Foundations of Quantum Bioinformatics 28712.3 Ethical Dimensions of Quantum Bioinformatics 28912.4 Equity and Justice in Quantum Bioinformatics 29012.5 Ecological Intelligence and Sustainability Considerations 29412.6 An Integrated Ethical–Equitable–Ecological Framework for Quantum Bioinformatics 29612.7 Conclusion 29912.8 Future Directions and Open Theoretical Challenges 300Bibliography 30113 Quantum-Secure and Sustainable Health Data: Integrating Privacy, Robustness, and Long-Term Viability in Bioinformatics-Driven AI Systems 303Vineetha B.13.1 Introduction 30413.2 Background Study 30613.3 Proposed Research: An Integrated Framework Based on the PRV Triad 31113.4 Test and Result Analysis 32213.5 Conclusion 331References 333Index 335