Introduction to Bioinformatics (SE446) Course Detail

Course Name	Course Code	Season	Lecture Hours	Application Hours	Lab Hours	Credit	ECTS
Introduction to Bioinformatics	SE446	Area Elective	3	0	0	3	5

Pre-requisite Course(s)
N/A

Course Language	English
Course Type	Elective Courses
Course Level	Bachelor’s Degree (First Cycle)
Mode of Delivery	Face To Face
Learning and Teaching Strategies	Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives	The objective of the course is to provide necessary knowledge and skills related to computational techniques for mining the large amount of biological data. In this course the applications of the computational techniques in bioinformatics will be introduced.
Course Learning Outcomes	The students who succeeded in this course; Apply DNA and protein sequence alignment techniques Build phylogenetic trees Apply techniques to predict protein structure Gain skills for clustering methods used in bioinformatics Analyze gene/protein networks
Course Content	DNA and protein sequence alignment, phylogenetic trees, protein structure prediction, motive findin, microarray data analysis, gene/protein networks.

Weekly Subjects and Releated Preparation Studies

Week	Subjects	Preparation
1	Introduction	Chapters 1,2,3 (main text)
2	Producing and Analyzing Sequence Alignments	Chapter 4
3	Pairwise Sequence Alignment and Database Searching	Chapter 5
4	Pairwise Sequence Alignment and Database Searching	Chapter 5
5	Patterns, Profiles, and Multiple Alignments	Chapter 6
6	Patterns, Profiles, and Multiple Alignments	Chapter 6
7	Recovering Evolutionary History	Chapter 7
8	Building Phylogenetic Trees	Chapter 8
9	Obtaining Secondary Structure from Sequence	Chapter 11
10	Predicting Secondary Structures	Chapter 12
11	Modeling Protein Structure	Chapter 13
12	Clustering Methods and Statistics	Chapter 16
13	Clustering Methods and Statistics	Chapter 16
14	Clustering Methods and Statistics	Chapter 17
15	Final Examination Period	Review of topics
16	Final Examination Period	Review of topics

Sources

Course Book	1. M. Zvelebil and J. O. Baum, Understanding Bioinformatics, Garland Science, 2008
Other Sources	2. N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT press, 2004
	3. A. M. Lesk, Introduction to Bioinformatics, Oxford University Press, 2002
	4. D. Mount, Bioinformatics: Sequence and genome analysis, Cold Spring Harbor Laboratory Press, 2001
	5. T. Jiang, Y. Xu, and M. Zhang, eds. Current Topics in Computational Molecular Biology, MIT press, 2002

Evaluation System

Requirements	Number	Percentage of Grade
Attendance/Participation	-	-
Laboratory	-	-
Application	-	-
Field Work	-	-
Special Course Internship	-	-
Quizzes/Studio Critics	-	-
Homework Assignments	1	20
Presentation	-	-
Project	1	30
Report	-	-
Seminar	-	-
Midterms Exams/Midterms Jury	1	20
Final Exam/Final Jury	1	30
Toplam	4	100

Percentage of Semester Work	70
Percentage of Final Work	30
Total	100

Course Category

Core Courses	X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

#	Program Qualifications / Competencies	Level of Contribution
#	Program Qualifications / Competencies	1	2	3	4	5
1	Gain sufficient knowledge in mathematics, science and computing; be able to use theoretical and applied knowledge in these areas to solve engineering problems related to information systems.			X
2	To be able to identify, define, formulate and solve complex engineering problems; to be able to select and apply appropriate analysis and modeling methods for this purpose.
3	Designs a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; applies modern design methods for this purpose.
4	To be able to develop, select and use modern techniques and tools required for the analysis and solution of complex problems encountered in information systems engineering applications; to be able to use information technologies effectively.			X
5	Designs and conducts experiments, collects data, analyzes and interprets results to investigate complex engineering problems or research topics specific to the discipline of information systems engineering.
6	Can work effectively in disciplinary and multidisciplinary teams; can work individually.					X
7	a. Communicates effectively both orally and in writing; writes effective reports and understands written reports, prepares design and production reports, makes effective presentations, gives and receives clear and understandable instructions. b. Knows at least one foreign language.
8	To be aware of the necessity of lifelong learning; to be able to access information, to be able to follow developments in science and technology and to be able to renew himself/herself continuously.
9	a. Acts in accordance with the principles of ethics, gains awareness of professional and ethical responsibility. b. Gains knowledge about the standards used in information systems engineering applications.
10	a. Gains knowledge about business life practices such as project management, risk management and change management. b. Gains awareness about entrepreneurship and innovation. c. Gains knowledge about sustainable development.
11	a. To be able to acquire knowledge about the universal and social effects of information systems engineering applications on health, environment and safety and the problems of the era reflected in the field of engineering. b. Gains awareness of the legal consequences of engineering solutions.

ECTS/Workload Table

Activities	Number	Duration (Hours)	Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)	16	3	48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class	16	2	32
Presentation/Seminar Prepration
Project
Report
Homework Assignments	3	5	15
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury	2	10	20
Prepration of Final Exams/Final Jury	1	15	15
Total Workload			130