MATH 400 | Course Introduction and Application Information

Course Name
Biomathematics
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
MATH 400
Fall/Spring
3
0
3
7

Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
First Cycle
Course Coordinator -
Course Lecturer(s) -
Assistant(s) -
Course Objectives This course introduces many mathematical models in biology. To use the mathematical tools like difference equations, differential equations, probability theory to model various biological phenomena, and also understand the basic analytical method based on calculus and algebra, qualitative analysis based on elementary geometry and computer aid numerical method to completely analize some basic models. These mathematical tools will be useful for life sciences major students in any quantitative and qualitative analysis in the future. Biological applications include various population growth models.
Learning Outcomes The students who succeeded in this course;
  • will be able to understand conceptual and visual representation of models.
  • will be able to understand population models.
  • will be able to analyze data in biological applications.
  • will be able to understand conceptual representation dynamic systems in biology.
  • will be able to understand and solve graph theory applications in biology.
Course Content Biological applications of difference and differantial equations. Biological applications of nonlinear differantial equations. Biological applications of graph theaory.

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Functions and mathematical models: Linear Models:Rate of mRNA synthesis,Quadratic models:Spread of a disease An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
2 Rational and Allometric models: Enzyme kinetics, Drug concentration, Cumulative AIDs cases An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
3 Discrete time dynamical systems: Cobwebbing, equilibrium, and stability, drug concentration An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
4 Biological Applications of Difference Equations An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
5 Discrete exponential and logistic growth: Growth of yeast cells, spread of a disease An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
6 Midterm Exam
7 Biological applications of differentail equations: Harvesting a single population An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
8 Biological applications of differentail equations: Harvesting a single population An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
9 Predatorprey models, Competiton models, Chemostat models An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
10 Epidemic models, Population Genetic models An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
11 Petri Nets An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
12 Probability and Stochastic Petri Nets An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
13 Applications of petri nets in bio An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
14 Term Project
15 Review for final exam
16 Review of the Semester  

 

Course Textbooks An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
References An Invitation to Biomathematics (9780120887712): Raina Stefanova Robeva, James R. Kirkwood, Robin Lee Davies, Leon Farhy, Boris P. Kovatchev, Academic Press, 2007

 

EVALUATION SYSTEM

Semester Requirements Number Percentage
Participation
1
5
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Homework / Assignments
2
10
Presentation / Jury
2
20
Project
1
15
Seminar / Workshop
Portfolios
Midterms / Oral Exams
1
20
Final / Oral Exam
1
30
Total

Contribution of Semester Work to Final Grade
6
70
Contribution of Final Work to Final Grade
1
30
Total

ECTS / WORKLOAD TABLE

Activities Number Duration (Hours) Workload
Course Hours
Including exam week: 16 x total hours
16
3
48
Laboratory / Application Hours
Including exam week: 16 x total hours
16
Study Hours Out of Class
15
5
Field Work
Quizzes / Studio Critiques
Homework / Assignments
2
15
Presentation / Jury
2
4
Project
1
10
Seminar / Workshop
Portfolios
Midterms / Oral Exams
1
14
Final / Oral Exam
1
20
    Total
205

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Qualifications / Outcomes
* Level of Contribution
1
2
3
4
5
1

To have sufficient background in Mathematics, Basic sciences and Biomedical Engineering areas and the skill to use this theoretical and practical background in the problems of the Biomedical Engineering.

2

To identify, formulate and solve Biomedical Engineering-related problems by using state-of-the-art methods, techniques and equipment; to select and apply appropriate analysis and modeling methods for this purpose.

3

To analyze a complex system, system components or process, and to design with realistic limitations to meet the requirements using modern design techniques; to apply modern design techniques for this purpose.

4

To choose and use the required modern techniques and tools for analysis and solution of complex problems in Biomedical Engineering applications; to skillfully use information technologies.

5

To design and do simulation and/or experiment, collect and analyze data and interpret results for studying complex engineering problems or research topics of the discipline. 

6

To efficiently participate in intradisciplinary and multidisciplinary teams; to work independently.

7

To communicate both in oral and written form in Turkish; to have knowledge of at least one foreign language; to have the skill to write and understand reports, prepare design and production reports, present, give and receive clear instructions.

8

To recognize the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.

9

To behave ethically, to be aware of professional and ethical responsibilities; to have knowledge about the standards in Biomedical Engineering applications.

10

To have information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.

11

To have knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of Biomedical Engineering solutions.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest