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
INE4011	System Simulation	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 :	Prof. Dr. MUSTAFA ÖZBAYRAK
Course Lecturer(s):	Prof. Dr. MUSTAFA ÖZBAYRAK RA ESRA ADIYEKE Prof. Dr. FAİK TUNÇ BOZBURA
Recommended Optional Program Components:	None
Course Objectives:	This course is designed for junior level Industrial Engineering and close disciplines' students to give the fundamental concepts of modelling and analysis of discrete systems. The course aims to provide rigorous input and output analyses of the simulation model created using the statistical and probabilistic concepts as well as modelling the discrete systems, with the examples from both manufacturing and service systems using a general purpose simulation software.

Learning Outcomes

The students who have succeeded in this course;
I. Recognize the basic principles of simulation modeling.
II. Define and use appropriate performance metrics when modeling a system.
III. Recognize the basic concepts of a discrete event simulation model including model components, flowchart, and event list.
IV. Collect and manage performance measurement data.
V. Data collection or production from a sample data set. Statistical analysis of the sample data to estimate or approximate the probabilistic distribution and its parameters.
VI. Modelling and analysis of discrete event simulation models of both manufacturing and service systems using generic simulation program called ARENA.
VII. Developing simulation models that address critical research issues and/or industrial systems.
VIII. Recognizing how a computer simulation program can be used to model complex systems and solve related decision problems under different working conditions, which are presented through several what-if scenarios and analyses.
IX. Running a simulation model under different scenarios through either short-term but with consecutive replications or one very long run to get turely random output and their statistical analyses.
X. Apply a simulation project from start to finish following the stages, data collection or generation, designing the model, building the model, creating the working scenarios, running the simulation with multiple replications and statistical analyses of the output generated.

Course Content

This course is an alternative modelling method to mathematical optimization to model the complex systems. This course aims to teach the fundamental principles of simulation modelling, its steps, data creation, design and create a simulation model with the help of a simulation software, running the model under different system scenarios, obtaining the output as well as analysing and reporting output.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to Simulation modeling
2)	A guided tour of modelling steps in Simulation.
3)	Statistics and Probability for Simulation Modelling I
4)	Statistics and Probability for Simulation Modelling II
5)	Modelling a simple system using ARENA
6)	System Modelling I
7)	System Modelling II
8)	Selecting the Input Analysis I
9)	Selecting Input Probability Distribution II
10)	System Modelling I
11)	Random Number Generation and Animasions
12)	Modelling Complex Systems
13)	Output Analysis
14)	Output Analysis II
15)	Entity Transfer in Modelling
16)	Simulation of Manufacturing Systems

Sources

Course Notes / Textbooks:	W. D. Kelton, R. P. Sadowski, D. T. Sturrock, Simulation with Arena-6th Edition, McGraw-Hill, 2015. J. Banks, J. S. Carson II, B. L. Nelson, D.M. Nicol, Discrete-Event System Simulation, 5th Edition, Prentice Hall, 2010.
References:	Lecture Notes and supporting materials collected from several academic resources as well as company reports and white papers.

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Quizzes	2	% 10
Homework Assignments	4	% 10
Project	1	% 20
Midterms	1	% 20
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Workload
Course Hours	14	28
Laboratory	14	28
Study Hours Out of Class	13	34
Project	3	9
Homework Assignments	2	6
Quizzes	2	18
Midterms	1	10
Final	1	12
Total Workload		145

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