Harnessing Artificial Intelligence-Enhanced Graph Models for Biological Discovery

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