molecular_informatics

Course Material for CHEM 4580/5580 Molecular Informatics, CU Denver, Prof. Scott Reed

Course Description:

This course resides at the intersection between Chemistry, Biochemistry, and Data Science. The course covers fundamental concepts of Chemical and Biochemical Informatics and provides students with hands on experience in using computational tools to manipulate chemical and biochemical data. Students will learn fundamentals of data science, database management, data structure, data representation, data visualization, and data analysis as applied to Chemistry and Biochemistry.

The course does not require extensive programming experience. Examples explored in class and in homework will be built using Python code within Jupyter Notebooks or Google Colab notebooks such that students can explore new topics while remaining focused on the underlying molecular concepts and computer methods which allow them to manage large amounts of molecular information and to find relationships between the structure and properties of molecules. Data mining approaches will be explored as will classification algorithms and chemical similarity analysis methods. Students will learn about the applications of cheminformatics in drug discovery, such as compound selection, virtual library generation, virtual high throughput screening which can check for potential molecules that have the potential to be developed into drugs. Throughout this course we will use artificial intelligence and large language models to speed our access to and understanding of these topics.

Prerequisite Knowledge: You should be comfortable with the first 3 sections of this tutorial: https://education.molssi.org/python_scripting_cms/