Courses Details

EHS687 Computational Toxicology

  • Graduate level
  • Fall term(s)
  • 2 Credit Hour(s)
  • Instructor(s): Richardson, Rudy
  • Not offered 2018-2019
  • Prerequisites: Organic Chemistry, Biochemistry, Biology, Introductory Toxicology
  • Description: Inquiry-based, hands-on problem solving in toxicology using computational approaches. After each lecture, students work in groups to solve toxicity-related problems in novel ways. Students will identify a problem, create a group project around the problem, and present a computationally based solution to the problem by the end of the semester.
  • Course Goals: 1. Present principles of computational toxicology 2. Present principles of predictive toxicology using computational tools 3. Provide opportunities for learning computationally based approaches for solving complex toxicological problems
  • Competencies: Students will be able to do the following: 1. Understand the basic principles of computational toxicology 2. Understand predictive toxicology using chemical structures and databases 3. Solve complex problems in new ways