COURSE INTRODUCTION AND APPLICATION INFORMATION


Course Name
Introduction to Bioinformatics
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
BME 310
Fall/Spring
2
2
3
5
Prerequisites
 GBE 100To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Elective
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course
Course Coordinator
Course Lecturer(s)
Assistant(s)
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;
  • Will be familiar with common bioinformatics tools and databases
  • Will be able to retrieve specific information in the literature or online databases,
  • Will be able to distinguish different types and formats of data,
  • Will be able to discuss common problems of bioinformatics,
  • Will be able to use basic bioinformatics tools for comparison of biological sequences and interpret results.
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
1 Introduction to bioinformatics Lecture notes
2 Gene structure and central dogma Chapter 1
3 ORF, intron splicing, types of mutations Chapter 1
4 Introduction to Pubmed databases Lecture notes
5 Literature search Lecture notes
6 FASTA and Genbank file format Chapter 5 and 6
7 BLASTn, BLASTp, tBLASTn chapter 6
8 Other alignment methods Lecture notes
9 Midterm
10 Multi Sequence Alignment using CLUSTALW Chapter 6
11 Phylogenetic relationships Chapter 9
12 SNP and haplotype analysis Chapter 7
13 Motif discovery and enrichment tools Lecture notes
14 Structural prediction of RNA Chapter 7
15 Structural protein database: PDB Lecture notes
16 Final Exam
Course Notes/Textbooks

Bioinformatics for beginners, Genes, Genomes, Molecular Evolution, Databases and Analytical Tools. Supratim Choudhuri. Elservier, 2014

N. C. Jones and P. A. Pevzner, An Introduction to Bioinformatics Algorithms, MIT press, 2004

Suggested Readings/Materials

Course material and online sources

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
5
40
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterm
1
30
Final Exam
1
30
Total

Weighting of Semester Activities on the Final Grade
6
70
Weighting of End-of-Semester Activities on the Final Grade
1
30
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
(Including exam week: 16 x total hours)
16
2
32
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
2
Study Hours Out of Class
15
2
30
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms
1
21
Final Exams
1
35
    Total
150

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have adequate knowledge in Mathematics, Science and Biomedical Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

X
2

To be able to identify, define, formulate, and solve complex Biomedical Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

4

To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Biomedical Engineering applications.

X
5

To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Biomedical Engineering research topics.

X
6

To be able to work efficiently in Biomedical Engineering disciplinary and multi-disciplinary teams; to be able to work individually.

7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions.

8

To have knowledge about global and social impact of Biomedical Engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of engineering solutions.

X
9

To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications.

10

To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Biomedical Engineering, and to be able to communicate with colleagues in a foreign language.

12

To be able to speak a second foreign language at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Biomedical Engineering.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest