Harnessing Artificial Intelligence-Enhanced Graph Models for Biological Discovery : Unveiling Biological Frontiers

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Harnessing Artificial Intelligence-Enhanced Graph Models for Biological Discovery : Unveiling Biological Frontiers

  • 言語:ENG
  • ISBN:9780443276088
  • eISBN:9780443276095

ファイル: /

Description

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

Table of Contents

1. Introduction to AI-powered graph models in biological sciencesSudan Jha and Chandan Upadhyaya2. Fundamentals of graph theory and biological networksEdgar Ceh-Varela and Sarbagya Ratna Shakya3. Leveraging Natural Language Processing and Graph Models for Sarcasm Detection in Text: Applications in Health Informatics and Biomedical ResearchManish Chandra Roy, Sukant Kishoro Bisoy and Pradipta Kumar Das4. Graph-Driven Machine Learning Frameworks for Survival Prediction in Colon Cancer GenomicsPinakshi Panda, Sukant Kishoro Bisoy and Subhendu Kumar Pani5. Network Modeling in Drug-Disease Systems Prediction: A ReviewMd. Alimul Haque, Farheen Islam, Sultan Ahmad, Md. Alamgir Hossain and Sangeeta Kumari6. Exploring Gene Expression Changes in Drosophila melanogaster with RNA-Sequencing Data AnalysisSarah Raza, Oroos Zohra, Md. Alimul Haque and Benazeer Zohra7. Biomedical Research Tools, Applications, and Case StudiesAman Anand, Praveen, Rajendra Kumar, Sudan Jha and Jaya Sinha8. Integrating Graph Neural Networks for Predictive Modeling in Complex Biological SystemsAnkit Bansal, Aman Anand, Nikita Verma, Neetu Singh and Rajendra Kumar9. Ethical Considerations in AI-Powered Healthcare and Data SecurityKritika Rana, Gaurav Gupta and Sultan Ahmad10. AI-Enhanced Drug Discovery and Repurposing Using Graph ModelsSangam Ghimire, Nirjal Bhurtel and Sudan Jha11. Intelligent Genetic Algorithm-Based Computational Neuroscience Model to Detect EpilepticHaewon Byeon, Azzah AlGhamdi, Ismail Keshta and Mukesh Soni

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