Department of Biomedical Engineering

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			X
LO2	Will be able to explain commonly used data formats in bioinformatics			X
LO3	Will be able to browse requested data using literature and databases				X
LO4	Will be able to use online bioinformatics tools				X
LO5	Will be able to Evaluate data obtained through bioinformatic methods			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