Department of Genetics and Bioengineering

BME 310 | Course Introduction and Application Information

Course Name

Introduction to Bioinformatics

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
BME 310	SPRING	2	2	3	5

Prerequisites	GBE 100 dersinden başarılı olmak (En az DD notu almış olmak)
Course Language	English
Course Type	ELECTIVE_COURSE
Course Level	First Cycle
Mode of Delivery	Face-To-Face
Teaching Methods and Techniques of the Course	-
National Occupational Classification Code	-
Course Coordinator	Doç. Dr. Osman Doluca
Course Lecturer(s)	Doç. Dr. Osman Doluca
Assistant(s)	Araş. Gör. Duygu Geçkin

Course Objectives

The objective of this course is to introduce most commonly used bioinformatics techniques, to comprehend basic terminology of bioinformatics, to analyze and visualize biological data, to find specific literature pertaining to topics of interest.

Learning Outcomes

The students who succeeded in this course;

Name	Description	PC Sub	* Contribution Level
Name	Description	PC Sub	1	2	3	4	5
LO1	Will be able to explain fundamental problems of bioinformatics	1.5		X
LO2	Will be able to explain commonly used data formats in bioinformatics	1.5		X
LO3	Will be able to browse requested data using literature and databases	5.1			X
LO4	Will be able to use online bioinformatics tools	4			X
LO5	Will be able to Evaluate data obtained through bioinformatic methods	5.3		X

Course Description

The course covers terminology used in bioinformatics, introduction to online and offline tools and databases, basic analysis techniques of biological sequences, comparison methods.

Related Sustainable Development Goals

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

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Required Materials	Learning Outcome
1	Introduction to bioinformatics	Lecture notes	LO1
2	Gene structure and central dogma	Choudhuri, S. (2014). Bioinformatics for beginners: genes, genomes, molecular evolution, databases and analytical tools. Elsevier. ISBN: 978-0-12-410471-6 Chapter 1	LO1
3	FASTA ve Genbank file formats	Choudhuri, S. (2014). Bioinformatics for beginners: genes, genomes, molecular evolution, databases and analytical tools. Elsevier. ISBN: 978-0-12-410471-6 Chapter 5	LO2
4	Structural protein database: PDB	Lecture notes and online resources	LO2
5	Exploring PubChem Substance and Compound Databases	Lecture notes and online resources	LO3
6	Chemical data formats: SMILES and SMARTS	Lecture notes and online resources	LO2
7	Literature search on PubMed	Lecture notes and online resources	LO3
8	Midterm		-
9	Genome tracking using GDV	Lecture notes and online resources	LO3
10	NCBI BLASTn, BLASTp, tBLASTn	Choudhuri, S. (2014). Bioinformatics for beginners: genes, genomes, molecular evolution, databases and analytical tools. Elsevier. ISBN: 978-0-12-410471-6 Chapter 5	LO4
11	Molecular dynamics and docking	Choudhuri, S. (2014). Bioinformatics for beginners: genes, genomes, molecular evolution, databases and analytical tools. Elsevier. ISBN: 978-0-12-410471-6 Chapter 1	LO2
12	Pairwise sequence alignment	Choudhuri, S. (2014). Bioinformatics for beginners: genes, genomes, molecular evolution, databases and analytical tools. Elsevier. ISBN: 978-0-12-410471-6 Chapter 6	LO4
13	Multi sequence alignment	Choudhuri, S. (2014). Bioinformatics for beginners: genes, genomes, molecular evolution, databases and analytical tools. Elsevier. ISBN: 978-0-12-410471-6 Chapter 6	LO5
14	Multi sequence alignment using CLUSTALW	Lecture notes and online resources	LO5
15	RNA structure prediction	Choudhuri, S. (2014). Bioinformatics for beginners: genes, genomes, molecular evolution, databases and analytical tools. Elsevier. ISBN: 978-0-12-410471-6 Chapter 7	LO4
16	Final Exam		-

Course Notes/Textbooks	Choudhuri S. (2014). Bioinformatics for beginners: genes genomes molecular evolution databases and analytical tools. Elsevier. ISBN: 978-0-12-410471-6
Suggested Readings/Materials	Jones N. C. & Pevzner P. A. (2004). An introduction to bioinformatics algorithms. MIT press. ISBN: 9780262101066

EVALUATION SYSTEM

Semester Activities	Number	Weighting	LO1	LO2	LO3	LO4	LO5
Laboratory / Application	1	40		X	X	X	X
Midterm	1	30	X	X	X
Final Exam	1	30	X	X	X	X	X
Total	3	100

ECTS / WORKLOAD TABLE

Semester Activities	Number	Duration (Hours)	Workload
Participation	-	-	-
Theoretical Course Hours	16	2	32
Laboratory / Application Hours	16	2	32
Study Hours Out of Class	14	2	28
Field Work	-	-	-
Quizzes / Studio Critiques	-	-	-
Portfolio	-	-	-
Homework / Assignments	-	-	-
Presentation / Jury	-	-	-
Project	-	-	-
Seminar / Workshop	-	-	-
Oral Exams	-	-	-
Midterms	1	23	23
Final Exam	1	35	35
		Total	150

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	1	2	3	4	5
1	Engineering Knowledge: Knowledge of mathematics, science, basic engineering, computation, and related engineering discipline-specific topics; the ability to apply this knowledge to solve complex engineering problems.
	1	Mathematics
	2	Science
	3	Basic Engineering
	4	Computation
	5	Related engineering discipline-specific topics		LO1 LO2
	6	The ability to apply this knowledge to solve complex engineering problems
2	Problem Analysis: Ability to identify, formulate and analyze complex engineering problems using basic knowledge of science, mathematics and engineering, and considering the UN Sustainable Development Goals relevant to the problem being addressed.
3	Engineering Design: The ability to devise creative solutions to complex engineering problems; the ability to design complex systems, processes, devices or products to meet current and future needs, considering realistic constraints and conditions.
	1	Ability to design creative solutions to complex engineering problems
	2	Ability to design complex systems, processes, devices or products to meet current and future needs, considering realistic constraints and conditions
4	Use of Techniques and Tools: Ability to select and use appropriate techniques, resources, and modern engineering and computing tools, including estimation and modeling, for the analysis and solution of complex engineering problems, while recognizing their limitations.				LO4
5	Research and Investigation: Ability to use research methods to investigate complex engineering problems, including literature research, designing and conducting experiments, collecting data, and analyzing and interpreting results.
	1	Literature research for the study of complex engineering problems			LO3
	2	Designing experiments
	3	Ability to use research methods, including conducting experiments, collecting data. analyzing and interpreting results		LO5
6	Global Impact of Engineering Practices: Knowledge of the impacts of engineering practices on society, health and safety, economy, sustainability, and the environment, within the context of the UN Sustainable Development Goals; awareness of the legal implications of engineering solutions.
	1	Knowledge of the impacts of engineering practices on society, health and safety, economy, sustainability, and the environment, within the context of the UN Sustainable Development Goals
	2	Awareness of the legal implications of engineering solutions
7	Ethical Behavior: Acting in accordance with the principles of the engineering profession, knowledge about ethical responsibility; awareness of being impartial, without discrimination, and being inclusive of diversity.
	1	Acting in accordance with the principles of the engineering profession, knowledge about ethical responsibility ethical responsibility
	2	Awareness of being impartial and inclusive of diversity, without discriminating on any subject
8	Individual and Teamwork: Ability to work effectively, individually and as a team member or leader on interdisciplinary and multidisciplinary teams (face-to-face, remote or hybrid).
	1	Ability to work individually and within the discipline
	2	Ability to work effectively as a team member or leader in multidisciplinary teams (face-to-face, remote or hybrid)
9	Verbal and Written Communication: Taking into account the various differences of the target audience (such as education, language, profession) on technical issues.
	1	Ability to communicate verbally
	2	Ability to communicate effectively in writing
10	Project Management: Knowledge of business practices such as project management and economic feasibility analysis; awareness of entrepreneurship and innovation.
	1	Knowledge of business practices such as project management and economic feasibility analysis
	2	Awareness of entrepreneurship and innovation
11	Lifelong Learning: Lifelong learning skills that include being able to learn independently and continuously, adapting to new and developing technologies, and thinking questioningly about technological changes.