BRE 672 - Biosystems Modeling Applications

Topic: INTRODUCTION

Instructor:

233 Gilmore Hall

737-6303

Office hours: T, Th 9-11, or anytime you can find me.

Course Objectives:

Develop skills in the development and application of deterministic and statistical models describing biotic and abiotic relationships. This course deals primarily with the simulation of complex ecological/biological systems. It is a very project-oriented class; much of the in-class time will be spent "hands-on" developing models.

Text:

Topics:

Students will be responsible for three areas:

1. Group Project: All students will participate in a group project, the topic of which will be decided collectively during the first week of class. The group project will be developed throughout the quarter, with specific benchmarks defined by the instructor. The project will involve the development of a fairly detailed simulation model, and will require the formulation of the conceptual approach, development of an implementation strategy, a team-based implementation effort, and a report on the results. It will emphasize model building in a team environment.

2. Individual Project: All students will develop an individual project, the topic of which will be decided by the student and approved by the instructor. The individual project will be developed throughout the quarter, with specific benchmarks defined by the instructor. The project will involve the development of a fairly detailed simulation model, and will require the formulation of the conceptual approach, development of an implementation strategy, a implementation effort, and a report on the results.

3. Topic Development: All students will lead a discussion of one a topic area related to simulation of biological systems. Specific topics will be determined collectively at the beginning of class. Each student will select a topic, develop lecture materials on the topic, and lead a group discussion on the topic. Topics to be considered include:
   • Use of Models in Decisionmaking
     
   • When Models Fail
     
   • Simulation Packages and Tools
     
   • Markov Models
     
   • Leslie Models for Age Class-based Simulations
     
   • Genetic Algorithms
     
   • Neural Networks
     

References:

• Law and Kelton, Simulation, Modeling and Analysis.
• Carnahan, Luther and Wilkes, Applied Numerical Methods.
• Conte and deBoor, Elementary Numerical Analysis
• Draper and Smith, Applied Regression Analysis
• Halfton, Theoretical Systems Ecology
• Hall and Day, Ecosystems Modeling in Theory and Practice
• O’Neill, Systems Ecology
• Keen and Spain, Computer Simulation in Biology

Grading:

1. Group Project - 40%
2. Individual Project - 40%
3. Topic Presentation - 20%

Copyright © 1996 John Bolte