INDUSTRIAL PRODUCTS DESIGN | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
GEN4059 | Computational Methods in Bioinformatics | Spring | 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 |
Recommended Optional Program Components: | There is none. |
Course Objectives: | The goal of this course is to provide an understanding of the fundamental computational methods used in bioinformatics and set of algorithms that have important applications in bioinformatics and also have several other applications outside of bioinformatics. |
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 through 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: | Relevant course notes or hand-outs will be supplied. |
References: | 1)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 | % 25 |
Midterms | 1 | % 25 |
Final | 1 | % 40 |
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 | 7 | 98 |
Midterms | 1 | 2 | 2 |
Final | 1 | 2 | 2 |
Total Workload | 144 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Having the theoretical and practical knowledge proficiency in the discipline of industrial product design | |
2) | Applying professional knowledge to the fields of product, service and experience design development | |
3) | Understanding, using, interpreting and evaluating the design concepts, knowledge and language | |
4) | Knowing the research methods in the discipline of industrial product design, collecting information with these methods, interpreting and applying the collected knowledge | |
5) | Identifying the problems of industrial product design, evaluating the conditions and requirements of problems, producing proposals of solutions to them | |
6) | Developing the solutions with the consideration of social, cultural, environmental, economic and humanistic values; being sensitive to personal differences and ability levels | |
7) | Having the ability of communicating the knowledge about design concepts and solutions through written, oral and visual methods | |
8) | To identify and apply the relation among material, form giving, detailing, maintenance and manufacturing methods of design solutions | |
9) | Using the computer aided information and communication technologies for the expression of industrial product design solutions and applications | |
10) | Having the knowledge and methods in disciplines like management, engineering, psychology, ergonomics, visual communication which support the solutions of industrial product design; having the ability of searching, acquiring and using the knowledge that belong these disciplines when necessary. | |
11) | Using a foreign language to command the jargon of industrial product design and communicate with the colleagues from different cultures | |
12) | Following and evaluating the new topics and trends that industrial product design needs to integrate according to technological and scientific developments |