CLICK HERE FOR THE COURSE SYLLABUS (.pdf)


COURSE INTRODUCTION AND APPLICATION INFORMATION

 
Course Name
Code
Semester
Theory
(hour/week)
Application/Laboratory
(hour/week)
Local Credits
ECTS
Biomathematics
MATH 663
Fall/Spring
3
0
3
7.5

Prerequisites
None

Course Language
English
Course Type
Elective
Course Level
Third Cycle
Course Coordinator -
Course Lecturer(s) -
Course Assistants -
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.
Course Learning Outcomes The students who succeeded in this course;
  • will be able to have a grasp of basic mathematics, applied mathematics and theories and applications of statistics.
  • will be able to use theoretical and applied knowledge acquired in the advanced fields of mathematics and statistics.
  • will be able to define and analyze problems and to find solutions based on scientific methods.
  • will be able to apply mathematics and statistics in real life with interdisciplinary approach and to discover their potentials.
  • will be able to criticize and renew her/his own models and solutions.
  • will be able to tell theoretical and technical information easily to both experts in detail and nonexperts in basic and comprehensible way.
  • will be familiar with computer programs used in the fields of mathematics and statistics and to be able to use at least one of them effectively.
  • will be able to behave in accordance with social, scientific and ethical values while applying solutions.
Course Content Biological applications of linear/nonlinear Difference Equations, theory and examples. Biological applications of  Linear/Nonlinear differential equations. Biological applications of partial differential equations. Biological applications of graph theory.

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Discrete time dynamical systems: Cobwebbing, equilibrium, and stability, drug concentration An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
2 Biological Applications of Differnce Equations An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
3 Discrete exponential and logistic growth: Growth of yeast cells, spread of a disease An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
4 Biological applications of differentail equations: Harvesting a single population An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
5 Biological applications of differentail equations: Harvesting a single population An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
6 Midterm Exam
7 Predatorprey models, Competiton models, An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
8 Epidemic models, Population Genetic models An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
9 Continuous age structured model An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
10 ReactionDiffusion equations An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
11 Equilibrium and traveling , wave solutions An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
12 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 Seminars
15 Review for final exam An Introduction to Mathematical Biology, Linda J.S.Allen,Pearson, 2007
16 Review of the Semester  

 

SOURCES

Course Notes / 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 of Grade
Attendance/Participation
Laboratory
Application
Field Work
Special Course Internship (Work Placement)
Quizzes/Studio Critics
Homework Assignments
Presentation/Jury
1
25
Project
Seminar/Workshop
Midterms/Oral Exams
1
35
Final/Oral Exam
1
40
Total

PERCENTAGE OF SEMESTER WORK
2
60
PERCENTAGE OF FINAL WORK
1
40
Total

 

COURSE CATEGORY

Course Category

Core Courses
Major Area Courses
X
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

 

THE RELATIONSHIP BETWEEN COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS

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

To develop and deepen his/her knowledge on theories of mathematics and statistics and their applications in level of expertise, and to obtain unique definitions which bring innovations to the area, based on master level competencies,

X
2

To have the ability of original, independent and critical thinking in Mathematics and Statistics and to be able to develop theoretical concepts,

X
3

To have the ability of defining and verifying problems in Mathematics and Statistics,

X
4

With an interdisciplinary approach, to be able to apply theoretical and applied methods of mathematics and statistics in analyzing and solving new problems and to be able to discover his/her own potentials with respect to the application,

X
5

In nearly every fields that mathematics and statistics are used, to be able to execute, conclude and report a research, which requires expertise, independently,

X
6

To be able to evaluate and renew his/her abilities and knowledge acquired in the field of Applied Mathematics and Statistics with critical approach, and to be able to analyze, synthesize and evaluate complex thoughts in a critical way,

X
7

To be able to convey his/her analyses and methods in the field of Applied Mathematics and Statistics to the experts in a scientific way,

X
8

To be able to use national and international academic resources (English) efficiently, to update his/her knowledge, to communicate with his/her native and foreign colleagues easily, to follow the literature periodically, to contribute scientific meetings held in his/her own field and other fields systematically as written, oral and visual.

X
9

To be familiar with computer software commonly used in the fields of Applied Mathematics and Statistics and to be able to use at least two of them efficiently,

X
10

To contribute the transformation process of his/her own society into an information society and the sustainability of this process by introducing scientific, technological, social and cultural advances in the fields of Applied Mathematics and Statistics,

X
11

As having rich cultural background and social sensitivity with a global perspective, to be able to evaluate all processes efficiently, to be able to contribute the solutions of social, scientific, cultural and ethical problems and to support the development of these values,

X
12

As being competent in abstract thinking, to be able to connect abstract events to concrete events and to transfer solutions, to analyze results with scientific methods by designing experiment and collecting data and to interpret them,

X
13

To be able to produce strategies, policies and plans about systems and topics in which mathematics and statistics are used and to be able to interpret and develop results,

X
14

To be able to evaluate, argue and analyze prominent persons, events and phenomena, which play an important role in the development and combination of the fields of Mathematics and Statistics, within the perspective of the development of other fields of science,

X
15

In Applied Mathematics and Statistics, to be able to sustain scientific work as an individual or a group, to be effective in all phases of an independent work, to participate decision-making process and to make and execute necessary planning within an effective time schedule.

X

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

ECTS / WORKLOAD TABLE

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
16
3
Laboratory
Application
Special Course Internship (Work Placement)
Field Work
Study Hours Out of Class
10
7
Presentations / Seminar
1
10
Project
Homework Assignments
Quizzes
Midterms / Oral Exams
1
10
Final / Oral Exam
1
40
    Total Workload

CLICK HERE FOR THE COURSE SYLLABUS (.pdf)

 
 

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