Course Title: Molecular Modeling and Machine Learning
Semester: Spring
Offered: 2023
Institution: Gyeongsang National University
Course Description:
This graduate-level course provides an in-depth exploration of molecular modeling and machine learning applications in bioinformatics and drug discovery. The course covers theoretical foundations and practical techniques, emphasizing structure-based drug design, pharmacophore modeling, and computational simulations. Students gain hands-on experience with software tools such as GROMACS, AutoDock, and Python libraries for machine learning, including scikit-learn and TensorFlow, to predict molecular interactions and pharmacokinetic properties.
Major Themes:
Fundamentals of molecular modeling and structure-based drug design
Machine learning applications in bioinformatics and predictive modeling
Pharmacophore modeling and virtual screening techniques
Molecular dynamics simulations and analysis
Prerequisites:
Students are expected to have a foundational understanding of molecular biology and introductory bioinformatics. Prior experience with Python programming is beneficial but not required, as an introductory module on Python basics will be provided.