LOGISTIC MANAGEMENT
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
MBG2004	Computation for Biological Sciences II	Spring Fall	2	2	3	7

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 :	Dr. Öğr. Üyesi ELIZABETH HEMOND
Course Lecturer(s):	Prof. Dr. SÜREYYA AKYÜZ
Course Objectives:	This class intended to provide advanced information to computational tools for biology.

Learning Outcomes

The students who have succeeded in this course;
1. Learn important biological data sources.
2. Evaluate the results of biological analysis statistically and mathematically.
3. Learns how to use various tools to evaluate genome sequencing data.
4. Learn basic level Matlab.

Course Content

Sequence data, searching and alignment, structural data, genome sequencing, genome analysis, genetic variation, gene and protein expression, and biological networks and pathways.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Advanced sequencing data analysis
2)	Genome alignment I
3)	Genome alignment II
4)	Structural data
5)	Genome sequencing
6)	Genome analysis I
7)	Genome analysis II
8)	Advanced genetic variation analysis I
9)	Advanced genetic variation analysis II
10)	Biological networks I
11)	Biological networks II
12)	Biological pathways I
13)	Biological pathways II
14)	Biological pathways III

Sources

Course Notes / Textbooks:	Ders notları haftalık olarak verilecektir. Course material will be provided weekly.
References:	Computational Biology Series Editors: Dress, A., Linial, M., Troyanskaya, O., Vingron, M. ISSN: 1568-2684

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Attendance	10	% 10
Presentation	1	% 15
Midterms	1	% 25
Final	1	% 50
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 50
PERCENTAGE OF FINAL WORK		% 50
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	4	56
Study Hours Out of Class	14	7	98
Presentations / Seminar	5	4	20
Midterms	1	2	2
Final	1	2	2
Total Workload			178

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)	To correctly identify the problems and to be able to ask the correct questions
2)	To have the ability for problem solving and to utilize analytical approach in dealing with the problems
3)	To be able to identify business processes and use them to increase the productivity in logistics system.
4)	To be fully prepared for a graduate study	2
5)	Awareness of the new advancements in Information and Communications Technologies (ICT) and to be able to use them in logistics management effectively. internet and the electronic world
6)	To understand the components of logistics as well as the importance of the coordination among these components.
7)	To know the necessary ingredients for improving the productivity in business life
8)	To think innovatively and creatively in complex situations	4
9)	To act and think both regionally and internationally
10)	To understand the demands and particular questions of globalization
11)	Aware of the two way interaction between globalization and logistics; as well as to use this interaction for increasing the productivity.
12)	To be able to use at least one foreign language both for communication and academic purposes	2
13)	To acquire leadership qualities but also to know how to be a team member
14)	To understand the importance of business ethics and to apply business ethics as a principal guide in both business and academic environment