Harnessing Artificial Intelligence-Enhanced Graph Models for Biological Discovery (eBook, ePUB)

Unveiling Biological Frontiers
Redaktion: Jha, Sudan; Pani, Subhendukumar; Ahmad, Sultan

• Format: ePub

Produktbeschreibung

Harnessing Artificial Intelligence-Enhanced Graph Models for Biological Discovery: Unveiling Biological Frontiers introduces revolutionary techniques that merge artificial intelligence with graph-based methods to uncover complex biological networks. Through detailed examples and case studies, the book provides researchers and practitioners the essential tools to analyze molecular interactions, identify key biomarkers, and hasten the discovery of novel therapeutics. Chapters delve into the sophisticated interplay between advanced AI techniques and graph models, specially designed to decode the intricacies of biological systems. By utilizing cutting-edge AI algorithms, readers can explore complex biological networks, forecast molecular interactions, and pinpoint new drug targets with exceptional precision. - Offers an innovative approach by combining artificial intelligence with graph-based techniques to delve into complex biological networks - Includes practical examples and case studies, providing researchers and practitioners with the tools they need to analyze molecular interactions and identify crucial biomarkers - Enables researchers to predict molecular interactions and identify novel drug targets with unparalleled accuracy and efficiency - Unlocks new avenues for biological discovery, facilitating precise and effective research outcomes

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 220
• Erscheinungstermin: 14. November 2025
• Englisch
• ISBN-13: 9780443276095
• Artikelnr.: 75806746

Inhaltsangabe

1. Introduction to AI-powered graph models in biological sciences
Sudan Jha and Chandan Upadhyaya
2. Fundamentals of graph theory and biological networks
Edgar Ceh-Varela and Sarbagya Ratna Shakya
3. Leveraging Natural Language Processing and Graph Models for Sarcasm
Detection in Text: Applications in Health Informatics and Biomedical
Research
Manish Chandra Roy, Sukant Kishoro Bisoy and Pradipta Kumar Das
4. Graph-Driven Machine Learning Frameworks for Survival Prediction in
Colon Cancer Genomics
Pinakshi Panda, Sukant Kishoro Bisoy and Subhendu Kumar Pani
5. Network Modeling in Drug-Disease Systems Prediction: A Review
Md. Alimul Haque, Farheen Islam, Sultan Ahmad, Md. Alamgir Hossain and
Sangeeta Kumari
6. Exploring Gene Expression Changes in Drosophila melanogaster with
RNA-Sequencing Data Analysis
Sarah Raza, Oroos Zohra, Md. Alimul Haque and Benazeer Zohra
7. Biomedical Research Tools, Applications, and Case Studies
Aman Anand, Praveen, Rajendra Kumar, Sudan Jha and Jaya Sinha
8. Integrating Graph Neural Networks for Predictive Modeling in Complex
Biological Systems
Ankit Bansal, Aman Anand, Nikita Verma, Neetu Singh and Rajendra Kumar
9. Ethical Considerations in AI-Powered Healthcare and Data Security
Kritika Rana, Gaurav Gupta and Sultan Ahmad
10. AI-Enhanced Drug Discovery and Repurposing Using Graph Models
Sangam Ghimire, Nirjal Bhurtel and Sudan Jha
11. Intelligent Genetic Algorithm-Based Computational Neuroscience Model to
Detect Epileptic
Haewon Byeon, Azzah AlGhamdi, Ismail Keshta and Mukesh Soni