Biological Modeling – BIO620 - Spring 2005

Dr. Tracy Galarowicz                          

Office: Brooks 184

Office phone: 774-1336

Email: galar1tl@cmich.edu

Office hours: Mon 2-3 p.m., Wed 11 a.m.- 1 p.m., or by appointment

Web page: http://www.cst.cmich.edu/users/galar1tl/

 

Class hours

Monday 12 – 2 p.m.

 

Course objectives

 

1.      Students will display knowledge of dynamic systems models.

2.      Students will apply different mathematical and simulation techniques to various systems.

3.      Students will use available tools for designing and analyzing models.

4.      Students will analyze the expected performance of models.

5.      Students will define a modeling problem and construct a model to address the identified problem.

 

Course text

Hannon, B. M., and M. Ruth.  2000.  Dynamic modeling: Modeling dynamic systems.  Springer-Verlag.

 

Grading

Homework

Discussion and participation

Modeling project (paper and presentation)

50% of grade

15% of grade

35% of grade

 

 

Final grades will be based on a tentative percentage scale:

A 92-100%, A- 90-92%, B+ 88-90%, B 82-88%, B- 80-82%, C+ 78-80%, C 72-78%,

C- 70-72%, D+ 68-70, D 60-69%, E <60%

 

Homework

Homework will be assigned regularly.  In most cases, electronic submission of homework assignments will be performed.  Homework assignments must include a brief description of the model being studies, a results section with numerical data or graphs, and a conclusions section summarizing what was learned about the particular biological system.

 

Discussion and participation

 

Students will be expected to participate in class discussions of readings.  Students will select a modeling paper and present the topic to the class.

Project and presentation

This course uses a problem based learning format in which students define, build, calibrate and run their own model.  A “publishable” report of the project and a presentation (including a demonstration of the model) during finals week will be due at the end of the semester.

 

Late assignments

For each day that a written assignment is late, 10% of the potential points will be deducted from that assignment.

 

Policy on Students with Disabilities

 

CMU provides students with disabilities reasonable accommodation to participate in educational programs, activities or services.  Students with disabilities requiring accommodation to participate in class activities or meet requirements should first register with the Office of Student Disability Services (250 Foust Hall, telephone #517-774-3018, TDD #2568), and then contact me as soon as possible.

 

 

Policy on Academic Integrity

 

In May 2001, the CMU Academic Senate approved the Policy on Academic Integrity, which applies to all university students.  Copies are available on the CMU website at http://academicsenate.cmich.edu/noncurric.htm, and in the Academic Senate Office in room 108 of Bovee University Center.  All academic work is expected to be in compliance with this policy.

 

Classroom Civility

 

Each CMU student is encouraged to help create an environment during class that promotes learning, dignity, and mutual respect for everyone.  Students who speak at inappropriate times, sleep in class, display inattention, take frequent breaks, interrupt the class by coming to class late, engage in loud or distracting behaviors, use cell phones or pagers in class, use inappropriate language, are verbally abusive, display defiance or disrespect to others, or behave aggressively toward others could be asked to leave the class and subjected to disciplinary action under the Code of Student Rights, Responsibilities and Disciplinary Procedures.

 

           

Tentative Schedule

Week

Date

Topics

1

Jan 10

Introduction to modeling, STELLA

 

2

Jan 17

No class – Martin Luther King, Jr. day

 

3

Jan 24

Population growth models

 

4

Jan 31

Intra- and Interspecific interaction models

 

5

Feb 7

Physiology models

 

6

Feb 14

Physiology models

 

7

Feb 21

Ecosystem models

 

8

Feb 28

Ecosystem models

 

9

Mar 14

Modeling individuals

 

10

Mar 21

Modeling individuals

 

11

Mar 28

Optimization models

 

12

Apr 4

Stochasticity and simulations

 

13

Apr 11

Prediction and parameter adjustment

 

14

Apr 18

Physiologically-structured models

 

15

Apr 25

Spatially-structured models

 

16

May 2

Final exam – Student presentations

 

 

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