PUBLIC RELATIONS AND PUBLICITY
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
GEN4059	Computational Methods 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
Recommended Optional Program Components:	There is none.
Course Objectives:	The goal of this course is to provide an understanding of the fundamental computational methods used in bioinformatics and set of algorithms that have important applications in bioinformatics and also have several other applications outside of bioinformatics.

Learning Outcomes

The students who have succeeded in this course;
1. Recognize the fundamental models of computation useful in modeling nucleic acid and protein sequences.
2. Design and implement algorithms useful for analyzing various molecular biology data.
3. Discuss Genetic Algorithm and its applications in bioinformatics.
4. Discuss Greedy Algorithms and its applications in bioinformatics.
5. Discuss Gibbs sampling and its applications in bioinformatics.
6. Recognize Expectation Maximization and its applications in bioinformatics.
7. Recognize Hidden Markov models and its applications in bioinformatics.
8. Define Bayesian networks and its applications in bioinformatics.
9. Define graphs and its applications in bioinformatics.

Course Content

This course will provide a broad and through background in computational methods and algorithms that are widely used in bioinformatics applications. Various existing methods will be critically described and the strengths and limitations of each will be discussed.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	A brief introduction to computational complexity and algorithm design techniques
2)	Exact sequence search algorithms
3)	Rabin-Karp algorithm, pattern matching, suffix trees
4)	Elements of dynamic programming, Manhattan tourist problem, k-band algorithm
5)	Approximate string matching, divide and conquer algorithms
6)	Branch and bound search
7)	Genetic Algorithm
8)	Greedy Algorithms
9)	Gibbs sampling
10)	Expectation Maximization
11)	Hidden Markov models
12)	Bayesian networks
13)	Graphs
14)	Review

Sources

Course Notes / Textbooks:	Relevant course notes or hand-outs will be supplied.
References:	1)An Introduction to Bioinformatics Algorithms (Computational Molecular Biology), Neil Jones and Pavel Pevzner, MIT Press, 2004.

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	2	% 10
Project	1	% 25
Midterms	1	% 25
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 35
PERCENTAGE OF FINAL WORK		% 65
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	7	98
Midterms	1	2	2
Final	1	2	2
Total Workload			144

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 prepare the students to become communication professionals by focusing on strategic thinking, professional writing, ethical practice and innovative use of traditional and new media
2)	To be able to create effective public relations plans using fundamental planning components that include situation analysis, public profile, objectives, strategies and tactics.
3)	To be able to apply theoretical concepts related to mass communication, consumer behavior, psychology, persuasion,sociology, marketing, and other related fields to understand how public realtions works.
4)	To be able to have the ability to explain and identify problems associated with the relationships between events and facts in the areas of public relations, persuasive communication, communication management, corporate communications.
5)	To be able to analyze primary and secondary research data in the fields of perception and reputation management and corporate communication practices.
6)	To be able to search, write, and design articles, newsletters, and fliers, brochures, and announcements, in styles and formats appropraite various audiences, mediums and settings.
7)	To be able to apply the underlying theories of communication and the necessities of work safety to different types of public relations processes and campaigns.
8)	To be able to develop creative and persuasive management skills in terms of reputation, employee relations, leadership and similar corporate practices.
9)	To be able to take responsibility in an individual capacity or as a team in generating solutions to given scenarios which can occur in public relations processes.
10)	To be able to understand how an organizational culture works and how employees and leaders create messages as a communication tool.
11)	To be able to critically discuss and interpret theories, concepts, methods, tools and ideas in the field of public relations.
12)	To be able to to use information, communication technologies and computer software with the required level of public relations, marketing communication, persuasive communication, communication management, corporate communications.
13)	To be able to explain and describe business marketing activities, economics, business law and global business practices.
14)	To be able to recognize national and international, social and cultural dimensions of public relations.