Information Package / Course Catalogue
Analytical Methods
Course Code: BYF507
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 1
Credit: 3
Lab: 0
ECTS: 4
Objectives of the Course

This course will provide understanding the analytical methods to solve real life biophysics problems. Ordinary and partial differential equations will be derived to describe the mathematical problems and solved analytically whenever possible with the help of symbolic algorithms and programming.

Course Content

This course will provide understanding the analytical methods to solve real life biophysics problems. Ordinary and partial differential equations will be derived to describe the mathematical problems and solved analytically whenever possible with the help of symbolic algorithms and programming.

Name of Lecturer(s)
Learning Outcomes
1.At the end of the course, students will be able to understand and comprehend problems in field of biophysics.
2.Students will be able to make the mathematical formulations of the problems, and will comprehend the methods to reach the functional and serial solutions analytically
3.To learn the symbolic programming with Mathematica and Matlab
4.To be able to comprehend the derivations of ordinary and partial differential equations concerning 1D, 2D and 3D problems
5.To be able to comprehend the use of canonical formulations and obtaining closed form solutions for the analysis of problems
Recommended or Required Reading
1.Related web sites
2.Related e-books
3.Related scientific articles
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to biophysics problems solvable analytically
Week 2 - Theoretical
Introduction to biophysics problems solvable analytically
Week 3 - Theoretical
Examples demonstrating the derivations of ordinary and partial differential equations concerning 1D, 2D and 3D problems
Week 4 - Theoretical
Examples demonstrating the derivations of ordinary and partial differential equations concerning 1D, 2D and 3D problems
Week 5 - Theoretical
Examples demonstrating the derivations of ordinary and partial differential equations concerning 1D, 2D and 3D problems
Week 6 - Theoretical
Generalized and Basis Functions used in solving in 1D, 2D and 3D problems
Week 7 - Theoretical
Generalized and Basis Functions used in solving in 1D, 2D and 3D problems
Week 8 - Intermediate Exam
Midterm exam
Week 9 - Theoretical
Symbolic Programming with Mathematica and Matlab
Week 10 - Theoretical
Symbolic Programming with Mathematica and Matlab
Week 11 - Theoretical
Symbolic Programming with Mathematica and Matlab
Week 12 - Theoretical
Conanical Formulations and Obtaining Closed Form Solutions for the example problems
Week 13 - Theoretical
Conanical Formulations and Obtaining Closed Form Solutions for the example problems
Week 14 - Theoretical
Conanical Formulations and Obtaining Closed Form Solutions for the example problems
Week 15 - Final Exam
Final exam
Assessment Methods and Criteria
Type of AssessmentCountPercent
Presentation1%2.5
Assignment1%2.5
Midterm Examination1%25
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory131239
Lecture - Practice131126
Assignment1516
Presentation 1516
Reading3116
Midterm Examination18210
Final Examination18210
TOTAL WORKLOAD (hours)103
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
PÇ-13
PÇ-14
PÇ-15
PÇ-16
PÇ-17
PÇ-18
OÇ-1
5
5
5
5
3
3
5
4
4
4
4
4
4
4
3
3
5
5
OÇ-2
5
5
5
5
3
3
5
4
4
4
4
4
4
4
3
3
5
5
OÇ-3
5
5
5
5
2
2
5
4
4
4
4
4
4
4
3
2
5
5
OÇ-4
5
5
5
5
3
2
5
3
3
4
4
4
4
4
3
2
4
4
OÇ-5
5
5
5
5
3
2
5
4
3
4
4
4
4
4
3
2
4
5
Adnan Menderes University - Information Package / Course Catalogue
2026