ECONOMICS
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	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)	As a world citizen, she is aware of global economic, political, social and ecological developments and trends.
2)	He/she is equipped to closely follow the technological progress required by global and local dynamics and to continue learning.
3)	Absorbs basic economic principles and analysis methods and uses them to evaluate daily events.
4)	Uses quantitative and statistical tools to identify economic problems, analyze them, and share their findings with relevant stakeholders.
5)	Understands the decision-making stages of economic units under existing constraints and incentives, examines the interactions and possible future effects of these decisions.
6)	Comprehends new ways of doing business using digital technologies. and new market structures.
7)	Takes critical approach to economic and social problems and develops analytical solutions.
8)	Has the necessary mathematical equipment to produce analytical solutions and use quantitative research methods.
9)	In the works he/she contributes, observes individual and social welfare together and with an ethical perspective.
10)	Deals with economic problems with an interdisciplinary approach and seeks solutions by making use of different disciplines.
11)	Generates original and innovative ideas in the works she/he contributes as part of a team.