MOLECULAR BIOLOGY AND GENETICS
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
MATH3012	Numerical Analysis	Fall	2	2	3	6

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :
Recommended Optional Program Components:	None
Course Objectives:	Numerical Analysis is concerned with the mathematical derivation, description and analysis of obtaining numerical solutions of mathematical problems. We have several objectives for the students. Students should obtain an intuitive and working understanding of some numerical methods for the basic problems of numerical analysis. They should gain some appreciation of the concept of error and of the need to analyze and predict it. And also they should develop some experience in the implementation of numerical methods by using a computer.

Learning Outcomes

The students who have succeeded in this course;

The students who succeeded in this course;
o will be able to define Errors, Big O Notation, Stability and Condition Number, Taylor’s Theorem.
o will be able to solve Nonlinear Equations.
o will be able to solve Linear Systems.
o will be able to use Iterative Methods for Linear Systems.
o will be able to calculate Eigenvalues and Eigenvectors.
o will be able to solve System of Nonlinear Equations.
o will be able to calculate Interpolating and Polynomial Approximation.

Course Content

In this course the solution of linear and nonlinear systems will be discussed numerically. Also iterative methods for linear systems will be taught.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Errors, Big O Notation, Stability and Condition Number, Taylor’s Theorem.
2)	The Solution of Nonlinear Equations in the form of f(x)=0: Bisection Method, Fixed Point Iteration.
3)	Newton-Rapson Method, Secant Method.
4)	The Solution of Linear System : Solving Triangular System, Gauss Elimination and Pivoting.
5)	LU Factorization, Tridiagonal System, Vector and Matrix Norms
6)	Sensitivity of Linear Equations. Condition Number and Stability.
7)	Iterative Methods for Linear Systems: Jacobi Method.
8)	Gauss Seidel Method. Diagonally Dominant Matrix. Errors in Solving Linear Systems.
9)	Eigenvalues and Eigenvectors: The Power Method. The Inverse Power Method.
10)	System of Nonlinear Equations: Newton’s Method.
11)	Interpolating and Polynomial Approximation: Lagrange interpolation polynomial, Newton Interpolation.
12)	Piecewise Linear Interpolation, Cubic Spline.
13)	Least Square Approximation: Curve Fitting.
14)	Inconsistent System of Equations. Errors in Interpolation .

Sources

Course Notes / Textbooks:	Numerical Methods Using MATLAB (Fourth Edition), John H. Mathews and Kurtis D. Fink, Pearson Prentice Hall
References:

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Attendance	16	% 0
Laboratory	16	% 5
Quizzes	5	% 10
Midterms	2	% 45
Final	1	% 45
Total		% 105
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 45
Total		% 105

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	16	3	48
Laboratory	14	1	14
Study Hours Out of Class	16	2	32
Quizzes	3	5	15
Midterms	2	5	10
Final	1	5	5
Total Workload			124

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Utilize the wealth of information stored in computer databases to answer basic biological questions and solve problems such as diagnosis and treatment of diseases.	3
2)	Acquire an ability to compile and analyze biological information, clearly present and discuss the conclusions, the inferred knowledge and the arguments behind them both in oral and written format.	4
3)	Develop critical, creative and analytical thinking skills.	5
4)	Develop effective communication skills and have competence in scientific speaking, reading and writing abilities in English and Turkish.	3
5)	Gain knowledge of different techniques and methods used in genetics and acquire the relevant laboratory skills.	4
6)	Detect biological problems, learn to make hypothesis and solve the hypothesis by using variety of experimental and observational methods.	4
7)	Gain knowledge of methods for collecting quantitative and qualitative data and obtain the related skills.	3
8)	Conduct research through paying attention to ethics, human values and rights. Pay special attention to confidentiality of information while working with human subjects.	5
9)	Obtain basic concepts used in theory and practices of molecular biology and genetics and establish associations between them.	4
10)	Search and use literature to improve himself/herself and follow recent developments in science and technology.	5
11)	Be aware of the national and international problems in the field and search for solutions.	4