COMPUTER ENGINEERING
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
CMP4131	Bioinformatics	Fall	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:	Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Dr. Öğr. Üyesi TARKAN AYDIN
Recommended Optional Program Components:	None
Course Objectives:	The course aims to teach the fundamental computational problems in molecular biology and genomics, the types and sources of data available for bioinformatics, a core set of widely used algorithms in bioinformatics.

Learning Outcomes

The students who have succeeded in this course;
I. Defining the fundamental computational problems in molecular biology and genomics
II. Understanding the types and sources of data available for bioinformatics
III. Implementing a core set of widely used algorithms in bioinformatics
IV. Understanding and comparing global, local and semi-global pairwise alignments.
V. Understanding and comparing PAM vs. BLOSSUM scoring matrices.
VI. Analyzing gene expression data.
VII. Recognizing protein folding problem
VIII. Analyzing protein-protein interaction networks.
IX. Implementing a set of algorithms that have important applications in bioinformatics, but which have key applications outside of biology as well.

Course Content

This course covers computational techniques for mining the large amount of information produced by recent advances in molecular biology, such as genome sequencing and microarrray technologies. The methods by which computers are used to manipulate and analyze sequences and structures will also be taught. The outline of the course is arranged to give fundamental concepts of bioinformatics to the students.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Review
1)	Introduction: Molecular Biology and Computer Science a) The organization of DNA, proteins, cell. b) In silico biology
2)	Pairwise alignment of biomolecular sequences and search for similarities: Global alignment of two sequences.
3)	Local alignment, Semi-global alignment.
4)	Scoring similarity matrices: BLOSSUM
5)	PAM similarity matrices
6)	Multiple sequence alignment a) Iterative Methods b) Structure Based Methods
7)	Scoring multiple alignments
8)	Bioinformatics approaches to gene expression, detecting differential expression
9)	Multiple hypothesis testing and false-discovery-rate methods for gene expression data.
10)	Protein Folding Problem: Simulated Annealing Algorithms
11)	Threading, Homology Modeling for Protein Folding Problem
12)	Protein-protein and protein/DNA interactions, Gene/Protein networks, pathways
13)	Construction and analysis of large scale biological networks
15)	Final
16)	Final

Sources

Course Notes / Textbooks:	Pevsner J., Bioinformatics and Functional Genomics, Wiley-Liss, 2009.
References:	Mount D.W., Bioinformatics: Sequence and Genome Analysis (2nd edition), Cold Spring Harbor Laboratory Press, 2004. Krane D.E., Raymer M.L., Fundamental Concepts of Bioinformatics, Benjamin Cummings, 2003.

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	2	% 10
Project	1	% 25
Midterms	1	% 30
Final	1	% 35
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	6	84
Midterms	1	2	2
Final	1	2	2
Total Workload			130

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)	Adequate knowledge in mathematics, science and computer engineering; the ability to use theoretical and practical knowledge in these areas in complex engineering problems.
2)	Ability to identify, formulate, and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose.
3)	Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose.
4)	Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in computer engineering applications; ability to use information technologies effectively.	4
5)	Ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or computer engineering research topics.	4
6)	Ability to work effectively within and multi-disciplinary teams; individual study skills.
7)	Ability to communicate effectively in verbal and written Turkish; knowledge of at least one foreign language; ability to write active reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8)	Awareness of the necessity of lifelong learning; ability to access information, to follow developments in science and technology and to renew continuously.
9)	To act in accordance with ethical principles, professional and ethical responsibility; information on the standards used in engineering applications.
10)	Information on business practices such as project management, risk management and change management; awareness of entrepreneurship and innovation; information about sustainable development.
11)	Knowledge of the effects of engineering practices on health, environment and safety in the universal and social scale and the problems of the era reflected in engineering; awareness of the legal consequences of engineering solutions.