BYM454 BioinformaticsInstitutional InformationDegree Programs Computer EngineeringInformation For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
Computer Engineering

Preview

Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course General Introduction Information

Course Code: BYM454
Course Name: Bioinformatics
Course Semester: Spring
Course Credits:
ECTS
6
Language of instruction:
Course Requirement:
Does the Course Require Work Experience?: No
Type of course: Departmental Elective
Course Level:
Bachelor TR-NQF-HE:6. Master`s Degree QF-EHEA:First Cycle EQF-LLL:6. Master`s Degree
Mode of Delivery: Face to face
Course Coordinator : Ar.Gör. MUHAMMED TAYYİP KOÇAK
Course Lecturer(s): Prof. Dr Halis Altun
Course Assistants:

Course Purpose and Content

Course Objectives: To teach the basic concepts and methods in the field of bioinformatics and to provide students with the ability to analyse biological data and develop related softw
Course Content: Introduction to biological data structures
Working with biological databases
DNA, RNA and protein sequence analyses
Genomic and proteomic data analysis techniques
Use of tools and software used in bioinformatics
Hands-on projects on real data

Learning Outcomes

The students who have succeeded in this course;
1) Students will learn the basic algorithms and methods used in bioinformatics.
2) Students will gain the ability to extract and analyse data from biological databases.
3) Students will be able to perform basic operations such as sequence alignment on biological data.
4) Students will be able to develop the necessary software for biological data analysis and use existing tools effectively.

Course Flow Plan

Week Subject Related Preparation
1) Introduction to Bioinformatics and Basic Concepts none
2) Biological Data Structures and Databases none
3) Sequence Alignment Techniques none
4) Genomic Data Analysis none
5) Protein Analysis Methods none
6) Analysis of Gene Expression none
7) Genetic Variation and Analysis none
8) Statistical Methods in Bioinformatics none
9) Machine Learning Applications none
10) Metagenomic Analyses none
11) Protein Structure Prediction and Analysis none
12) Systems Biology and Network Analyses none
13) Current Research Topics and New Technologies none
14) Presentation and Evaluation of Final Projects none

Sources

Course Notes / Textbooks: yok
References: none

Course - Learning Outcome Relationship

No Effect 1 Lowest 2 Medium 3 Highest
       
Program Outcomes Level of Contribution
1) Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in complex engineering problems.
2) Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
3) Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose
4) Ability to devise, select, and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively.
5) Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions.
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively in Turkish, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
8) Knowledge of the global and societal impacts of engineering practices on priority issues such as health, environment and safety and contemporary issues; knowledge of the legal aspects of engineering solutions. awareness of the consequences
9) Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice.
10) Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and knowledge about sustainable development.
11) Ability to design systems to meet desired needs
12) Ability to apply basic sciences in the field of computer engineering
13) Ability to implement designs by experiments
14) Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.

Learning Activity and Teaching Methods

Bireysel çalışma ve ödevi
Course
Homework

Measurement and Evaluation Methods and Criteria

Yazılı Sınav (Açık uçlu sorular, çoktan seçmeli, doğru yanlış, eşleştirme, boşluk doldurma, sıralama)
Homework

Assessment & Grading

Semester Requirements Number of Activities Level of Contribution
Homework Assignments 1 % 20
Midterms 1 % 30
Final 1 % 50
total % 100
PERCENTAGE OF SEMESTER WORK % 50
PERCENTAGE OF FINAL WORK % 50
total % 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities Number of Activities Aktiviteye Hazırlık Aktivitede Harçanan Süre Aktivite Gereksinimi İçin Süre Workload
Course Hours 14 3 42
Homework Assignments 3 25 75
Midterms 1 25 25
Final 1 30 30
Total Workload 172