ECONOMICS | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
MBG4059 | Computational Methods in Bioinformatics | Fall | 3 | 0 | 3 | 6 |
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Language of instruction: | English |
Type of course: | Non-Departmental Elective |
Course Level: | Bachelor’s Degree (First Cycle) |
Mode of Delivery: | Face to face |
Course Coordinator : | Dr. Öğr. Üyesi ELIZABETH HEMOND |
Course Objectives: | The goal of this course is to provide an understanding of the fundamental computational methods used in bioinformatics and the set of algorithms that have important applications both inside and outside of the bioinformatics field. |
The students who have succeeded in this course; 1. Recognize the fundamental models of computation useful in modeling nucleic acid and protein sequences. 2. Design and implement algorithms useful for analyzing various molecular biology data. 3. Discuss Genetic Algorithm and its applications in bioinformatics. 4. Discuss Greedy Algorithms and its applications in bioinformatics. 5. Discuss Gibbs sampling and its applications in bioinformatics. 6. Recognize Expectation Maximization and its applications in bioinformatics. 7. Recognize Hidden Markov models and its applications in bioinformatics. 8. Define Bayesian networks and its applications in bioinformatics. 9. Define graphs and its applications in bioinformatics. |
This course will provide a broad and thorough background in computational methods and algorithms that are widely used in bioinformatics applications. Various existing methods will be critically described and the strengths and limitations of each will be discussed. |
Week | Subject | Related Preparation |
1) | A brief introduction to computational complexity and algorithm design techniques | |
2) | Exact sequence search algorithms | |
3) | Rabin-Karp algorithm, pattern matching, suffix trees | |
4) | Elements of dynamic programming, Manhattan tourist problem, k-band algorithm | |
5) | Approximate string matching, divide and conquer algorithms | |
6) | Branch and bound search | |
7) | Genetic Algorithm | |
8) | Greedy Algorithms | |
9) | Gibbs sampling | |
10) | Expectation Maximization | |
11) | Hidden Markov models | |
12) | Bayesian networks | |
13) | Graphs | |
14) | Review |
Course Notes / Textbooks: | Haftalık ders notları iletilecektir. Weekly course notes will be provided. |
References: | An Introduction to Bioinformatics Algorithms (Computational Molecular Biology), Neil Jones and Pavel Pevzner, MIT Press, 2004. |
Semester Requirements | Number of Activities | Level of Contribution |
Homework Assignments | 2 | % 10 |
Project | 1 | % 15 |
Midterms | 1 | % 25 |
Final | 1 | % 50 |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 35 | |
PERCENTAGE OF FINAL WORK | % 65 | |
Total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 14 | 3 | 42 |
Study Hours Out of Class | 14 | 6 | 84 |
Presentations / Seminar | 5 | 4 | 20 |
Midterms | 1 | 2 | 2 |
Final | 1 | 2 | 2 |
Total Workload | 150 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | As a world citizen, she is aware of global economic, political, social and ecological developments and trends. | 2 |
2) | He/she is equipped to closely follow the technological progress required by global and local dynamics and to continue learning. | 2 |
3) | Absorbs basic economic principles and analysis methods and uses them to evaluate daily events. | 2 |
4) | Uses quantitative and statistical tools to identify economic problems, analyze them, and share their findings with relevant stakeholders. | 2 |
5) | Understands the decision-making stages of economic units under existing constraints and incentives, examines the interactions and possible future effects of these decisions. | 1 |
6) | Comprehends new ways of doing business using digital technologies. and new market structures. | 2 |
7) | Takes critical approach to economic and social problems and develops analytical solutions. | 1 |
8) | Has the necessary mathematical equipment to produce analytical solutions and use quantitative research methods. | 2 |
9) | In the works he/she contributes, observes individual and social welfare together and with an ethical perspective. | 2 |
10) | Deals with economic problems with an interdisciplinary approach and seeks solutions by making use of different disciplines. | 1 |
11) | Generates original and innovative ideas in the works she/he contributes as part of a team. | 2 |