| MATHEMATICS (TURKISH, PHD) | |||||
| PhD | TR-NQF-HE: Level 8 | QF-EHEA: Third Cycle | EQF-LLL: Level 8 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| GEN2006 | Computational Biology | Fall | 3 | 2 | 4 | 8 |
| The course opens with the approval of the Department at the beginning of each semester |
| Language of instruction: | En |
| Type of course: | Departmental Elective |
| Course Level: | |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Dr. Öğr. Üyesi ELIZABETH HEMOND |
| Course Lecturer(s): |
Prof. Dr. SÜREYYA AKYÜZ |
| Course Objectives: | This course aims to provide an understanding of the types and sources of data available for computational biology, the fundamental computational problems in molecular biology and genomics and a core set of widely used algorithms in computational biology. |
|
The students who have succeeded in this course; 1. Discuss how to measure the similarity between two given proteins. 2. Calculate how to measure the differences between various DNA sequences. 3. Discuss how to quantify the significance of the differences between sequences. 4. Recognize how to determine the likelihood that such a similarity relationship could occur by chance. 5. Define how to perform a search based on sequence similarity. 6. Analyze how to generate multiple sequence alignments. 7. Define how to create phylogenetic trees. 8. Discuss the genomic variations between individuals, and their effect on disease. 9. Utilize the pathway elucidation techniques. |
| Computational biology involves the development and application of computational methods in order to address the problems in molecular biology. Students will practice on software programming of the algorithms studied in the course (in simplified settings) as well as get experience in using sequence analysis tools available either locally or via Internet. |
| Week | Subject | Related Preparation | |
| 1) | Basic Concepts of Molecular Biology; Nucleic acid world, Proteins. | ||
| 2) | The Mechanisms of Molecular Genetics; Genes and the Genetic Code, Transcription, Translation and Protein Synthesis, junk DNA and Reading frames, Chromosomes. | ||
| 3) | Sequence Alignment Algorithms: Needleman–Wunsch algorithm, Semiglobal Alignment. | ||
| 4) | Sequence Alignment Algorithms: Smith-Waterman algorithm. | ||
| 5) | Multiple Sequence Alignment; Star alignment, Tree alignment. | ||
| 6) | Multiple alignment of conservative sequence domains. Gibbs sampling algorithm for multiple sequence alignment. Algorithms for prediction of functional sites in DNA sequences (RBS sites, promoters, splice sites). | ||
| 7) | PAM, BLOSSUM scoring matrices. | ||
| 8) | Database Search: BLAST, FASTA. | ||
| 9) | Phylogenetic Trees; Character State Matrices, Reconstructing Additive Trees. | ||
| 10) | Human genetic variations, Single Nucleotide Polymorphisms and medicine. | ||
| 11) | Genome-wide association studies. | ||
| 12) | Pathway Elucidation Techniques and Tools. | ||
| 13) | Biological Networks | ||
| 14) | Review | ||
| Course Notes: | Relevant notes or hand-outs will be supplied. |
| References: | 1)Jones N. C. and Pevzner P. A., An Introduction to Bioinformatics Algorithms, MIT press, 2004. 2)Pevzner P.A., Computational Molecular Biology: An Algorithmic Approach, MIT Press, 2000. 3)Zvelebil M., Baum J.O., Understanding Bioinformatics, Garland Science, 2008. 4)Setubal C., Meidanis J., Introduction to Computational Molecular Biology, PWS Publishing, 1997. |
| Semester Requirements | Number of Activities | Level of Contribution |
| Attendance | % 0 | |
| Laboratory | 12 | % 20 |
| Application | % 0 | |
| Field Work | % 0 | |
| Special Course Internship (Work Placement) | % 0 | |
| Quizzes | % 0 | |
| Homework Assignments | 2 | % 15 |
| Presentation | % 0 | |
| Project | % 0 | |
| Seminar | % 0 | |
| Midterms | 1 | % 25 |
| Preliminary Jury | % 0 | |
| Final | 1 | % 40 |
| Paper Submission | % 0 | |
| Jury | % 0 | |
| Bütünleme | % 0 | |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 60 | |
| PERCENTAGE OF FINAL WORK | % 40 | |
| Total | % 100 | |
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 14 | 2 | 28 |
| Laboratory | 14 | 2 | 28 |
| Application | 0 | 0 | 0 |
| Special Course Internship (Work Placement) | 0 | 0 | 0 |
| Field Work | 0 | 0 | 0 |
| Study Hours Out of Class | 14 | 8 | 112 |
| Presentations / Seminar | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Homework Assignments | 0 | 0 | 0 |
| Quizzes | 0 | 0 | 0 |
| Preliminary Jury | 0 | ||
| Midterms | 1 | 2 | 2 |
| Paper Submission | 0 | ||
| Jury | 0 | ||
| Final | 1 | 2 | 2 |
| Total Workload | 172 | ||
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution |