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
Fall/Spring
2
2
3
5

Prerequisites
  GBE 100 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Elective
Course Level
First Cycle
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 Content The course covers terminology used in bioinformatics, introduction to online and offline tools and databases, basic analysis techniques of biological sequences, comparison methods.

 



Course Category

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

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
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 Review

 

Course 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

References

Course material and online sources

 

EVALUATION SYSTEM

Semester Requirements Number Percentage
Participation
1
10
Laboratory / Application
1
30
Field Work
Quizzes / Studio Critiques
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Portfolios
Midterms / Oral Exams
1
20
Final / Oral Exam
1
40
Total

Contribution of Semester Work to Final Grade
3
60
Contribution of Final Work to Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

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
3
Field Work
Quizzes / Studio Critiques
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Portfolios
Midterms / Oral Exams
1
16
Final / Oral Exam
1
25
    Total
150

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

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

To have sufficient background in Mathematics, Basic sciences and Biomedical Engineering areas and the skill to use this theoretical and practical background in the problems of the Biomedical Engineering.

X
2

To identify, formulate and solve Biomedical Engineering-related problems by using state-of-the-art methods, techniques and equipment; to select and apply appropriate analysis and modeling methods for this purpose.

X
3

To analyze a complex system, system components or process, and to design with realistic limitations to meet the requirements using modern design techniques; to apply modern design techniques for this purpose.

X
4

To choose and use the required modern techniques and tools for analysis and solution of complex problems in Biomedical Engineering applications; to skillfully use information technologies.

X
5

To design and do simulation and/or experiment, collect and analyze data and interpret results for studying complex engineering problems or research topics of the discipline. 

X
6

To efficiently participate in intradisciplinary and multidisciplinary teams; to work independently.

7

To communicate both in oral and written form in Turkish; to have knowledge of at least one foreign language; to have the skill to write and understand reports, prepare design and production reports, present, give and receive clear instructions.

8

To recognize the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.

X
9

To behave ethically, to be aware of professional and ethical responsibilities; to have knowledge about the standards in Biomedical Engineering applications.

10

To have information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.

11

To have knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of Biomedical Engineering solutions.

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