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
MBG4057	Special Topics in Bioinformatics	Spring	3	0	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 :	Dr. Öğr. Üyesi ELIZABETH HEMOND
Course Objectives:	This course aims to discuss technical papers from the recent bioinformatics literature, examine their algorithms and conduct an intensive study on a specific bioinformatics problem.

Learning Outcomes

The students who have succeeded in this course;
1. Define the open research questions in bioinformatics.
2. Discuss current solutions to tackle bioinformatics problems.
3. Develop an ability to discuss open research issues in computational biology.
4. Acquire an understanding of existing bioinformatics solutions for genomics.
5. Acquire an understanding of existing bioinformatics solutions for proteomics.
6. Develop an ability to focus on several bioinformatics articles and present their findings.
7. Obtain a familiarity with emerging topics in bioinformatics.
8. Obtain a familiarity with emerging topics in computational biology.
9. Develop an ability to find, read and discuss scientific articles published in the bioinformatics field.

Course Content

This discussion-based bioinformatics course will expose students to the latest developments in bioinformatics analyses and algorithms.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Genomics (genome sequencing, storage and study of genome information, genome databases)
2)	Genomics (polymorphism in the human genome and association with diseases)
3)	Comparative genomics (genome subtraction method, whole-genome alignment methods, genome-context methods, gene-fusion method)
4)	Structural genomics (the scientific program of structural genomics, target selection in structural genomics)
5)	Functional genomics (integration of experimental and computational methods)
6)	Functional genomics (gene-expression data and DNA micro-arrays)
7)	Functional genomics (regulatory networks, protein-protein interaction networks)
8)	Proteomics, Protein folding and fold recognition
9)	Epigenomics
10)	Cancer informatics
11)	Non-coding RNA identification and search
12)	Emerging topics in bioinformatics
13)	Emerging topics in computational biology
14)	Presentations

Sources

Course Notes / Textbooks:	Haftalık ders notları iletilecektir. Course notes will be supplied.
References:	Articles from the primary literature (scientific journals, e.g. Nature Reviews Genetics, Nature, Science, Genome Research, Nature Genetics, Nature Methods, Bioinformatics, Molecular Systems Biology etc.)

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	2	% 15
Project	1	% 25
Midterms	1	% 10
Final	1	% 50
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 25
PERCENTAGE OF FINAL WORK		% 75
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	8	112
Midterms	1	2	2
Final	1	2	2
Total Workload			158

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.