MEB713 - STRUCTURE and FORMATION MECHANISMS of GENOME VARIATIONS
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| STRUCTURE and FORMATION MECHANISMS of GENOME VARIATIONS | MEB713 | Any Semester/Year | 3 | 0 | 3 | 7 |
| Prequisites | Limited to a quota of 10 students | |||||
| Course language | Turkish | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Discussion Team/Group Work Other: Project Design, Presentation | |||||
| Instructor (s) | Prof. Pervin DİNÇER | |||||
| Course objective | After completing this course, students will learn the effects of genome variation in molecular pathology and they will gain knowledge about the mechanisms of genome variations. | |||||
| Learning outcomes |
| |||||
| Course Content | In this course, the lectures will be given on classification of genome variations such as small or large, rare or common, pathogenic or nonpathogenic, somatic or germ line, inherited or de novo; SNV, indel, CNV, de novo and other different genome variations and their mechanisms, nomenclature of the genome variations and databases related to genome variation, consortia (HapMap, 2000 genome, ENCODE, etc.), Within the scope of this course, students will discuss five review or research articles. In addition, a project will be designed by the students as a group work related to the processes needed to show the effects of different types of DNA variations. | |||||
| References | 1. Cooper DN, Krawczak M, Human Gene Mutation, Bios Scientific Publishers, 1993. 2. Brown TA Genomes, Bios Scientific Publishers, 1999. 3. Strachan T, Tead AP, Human Molecular Genetics, Garland Science, Taylor and Francis Group, 2011. | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Description/definition and classification of genomic variations/SNV (single nucleotide variation), CNV (copy number variations) and indels (insertions deletions variations) |
| Week 2 | SNVs and formation mechanisms |
| Week 3 | Paper discussion (Presentation) |
| Week 4 | CNVs, and formation mechanisms |
| Week 5 | Paper discussion (Presentation) |
| Week 6 | Paper discussion (Presentation) |
| Week 7 | Indel variation and formation mechanisms |
| Week 8 | Paper discussion (Presentation) |
| Week 9 | De novo mutations |
| Week 10 | Paper discussion (Presentation) |
| Week 11 | Naming properties of the genome variations in the literature and related databases |
| Week 12 | Genome Consortia (OMIM, HUGO, DbSNP, HapMap, 2000 genome, GWAS, ENCODE, etc.) |
| Week 13 | Genome Consortia (OMIM, HUGO, DbSNP, HapMap, 2000 genome, GWAS, ENCODE, etc.) |
| Week 14 | Project presentations |
| Week 15 | Preparation for the final exam |
| Week 16 | Final exam |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 0 | 0 |
| Laboratory | 0 | 0 |
| Application | 0 | 0 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 0 | 0 |
| Presentation | 5 | 20 |
| Project | 1 | 30 |
| Seminar | 0 | 0 |
| Midterms | 0 | 0 |
| Final exam | 1 | 50 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 6 | 50 |
| Percentage of final exam contributing grade succes | 1 | 50 |
| Total | 100 | |
WORKLOAD AND ECTS CALCULATION
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 14 | 3 | 42 |
| Laboratory | 0 | 0 | 0 |
| Application | 0 | 0 | 0 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 14 | 8 | 112 |
| Presentation / Seminar Preparation | 5 | 5 | 25 |
| Project | 1 | 12 | 12 |
| Homework assignment | 0 | 0 | 0 |
| Midterms (Study duration) | 0 | 0 | 0 |
| Final Exam (Study duration) | 1 | 15 | 15 |
| Total Workload | 35 | 43 | 206 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. Doctorate candidates are trained as a scientist and educated and experienced with the knowledge on inherited metabolic diseases, they will be able to perform advanced analytical chemistry and molecular genetics methods. | X | ||||
| 2. Doctorate candidates will be qualified at the end of the program as a result of applying laboratory experiments and studies during their thesis studies, earning theoretical knowledge from lectures , and they can continue their research activities as an independent researcher. | X | ||||
| 3. They are informed with good laboratory practices and the biosafety rules and they obey these rules for their laboratory studies. They will be knowledged for iterpretation of the primary and advanced metabolic and molecular genetics tests and experiments for thediagnosis of inherited metabolic diseases | X | ||||
| 4. They can develop new technologies which can be used for identification of metabolic diseases at the national level. They can work for development of new methods for metabolic screening programs. | X | ||||
| 5. They can criticise their own knowledge as a qualified scientist who are able to plans original research and applies it, they can apply and obey ethical rules in their studies working with a team or alone. | X | ||||
| 6. Multidiciplinary approach are needed for Metabolism research. This study area is known as biochemical genetics and requires to apply many different research activities together in the field of molecular genetics, anlytical chemistry, biochemistry, genetics, molecular cell biology. At the end of the program, trainees will be qualified on basic principles of these fields and experienced with the application of different laboratory methodologies. | X | ||||
| 7. Graduate students works in an atmosphere which is designed for interdiciplinary team research. | X | ||||
| 8. They can follow up recent advances in the field of molecular metabolism and literature at international level. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest