ARTIFICIAL INTELLIGENCE 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
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)	Have sufficient background in mathematics, science and artificial intelligence engineering.
2)	Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions.
3)	Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose.
4)	Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction.
5)	Select and use modern techniques and tools necessary for engineering applications.
6)	Design and conduct experiments, collect data, and analyse and interpret results.
7)	Work effectively both as an individual and as a multi-disciplinary team member.
8)	Access information via conducting literature research, using databases and other resources
9)	Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning.
10)	Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field.
11)	Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level.
12)	Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age.
13)	Have a sense of professional and ethical responsibility.
14)	Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices.