BIO508 Advanced Genetic Engineering
Syllabus | International University of Sarajevo - Last Update on Feb 02, 2026
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Genetics and Bioengineering
Jasmin Šutković
Course Lecturer
Course Objectives
Introduce students to advanced topics in genetic engineering, including recent advancements in the field.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
Research articles.
Additional Literature
Research the articles and materials provided by the professor.Teaching Methods
Lectures
Presentations
Video tutorials
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction to the Course | TBD |
| 2 | How to write article journal paper and search the databases! | TBD |
| 3 | Assignment Presentations 1 | TBD |
| 4 | Assignment Presentations 2 | TBD |
| 5 | Assignment Presentations 3 | TBD |
| 6 | Assignment Presentations 4 | TBD |
| 7 | Assignment Presentations 5 | TBD |
| 8 | MIDTERM PROJECT | - |
| 9 | Assignment Presentations 6 | TBD |
| 10 | Assignment Presentations 7 | TBD |
| 11 | Assignment Presentations 8 | TBD |
| 12 | Assignment Presentations 9 | TBD |
| 13 | Assignment Presentations 10 | TBD |
| 14 | Assignment Presentations 11 | TBD |
| 15 | FINAL PROJECT | - |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| BIO508.1 | Course | Monday 11:00 - 13:50 | A F1.11 | - | - |
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Tuesday | 09:00 - 12:00 | A F1.13 | Or any time via teams |
| Thursday | 09:00 - 11:00 | A F1.13 | Or any time via teams |
Assessment Methods and Criteria
Assessment Components
Final Project
AI: Consult InstructorAlignment with Learning Outcomes : 1 2 3 4 5
Assignments
AI: Consult InstructorAlignment with Learning Outcomes : 1 2 3
Midterm project
AI: Consult InstructorAlignment with Learning Outcomes : 1 2 3 4
IUS Grading System
| Grading Scale | IUS Grading System | IUS Coeff. | Letter (B&H) | Numerical (B&H) |
|---|---|---|---|---|
| 0 - 44 | F | 0 | F | 5 |
| 45 - 54 | E | 1 | ||
| 55 - 64 | C | 2 | E | 6 |
| 65 - 69 | C+ | 2.3 | D | 7 |
| 70 -74 | B- | 2.7 | ||
| 75 - 79 | B | 3 | C | 8 |
| 80 - 84 | B+ | 3.3 | ||
| 85 - 94 | A- | 3.7 | B | 9 |
| 95 - 100 | A | 4 | A | 10 |
Late Work Policy
Information about late submission policies will be shared during class and posted in this section. Please check back for official guidelines.
ECTS Credit Calculation
📚 Student Workload
This 6 ECTS credit course corresponds to 150 hours of total student workload, distributed as follows:
Lectures
45 hours ⏳ (15 week × 3 h)
Asignment
25 hours ⏳ (5 week × 5 h)
Presentation
20 hours ⏳ (5 week × 4 h)
Home Study
30 hours ⏳ (10 week × 3 h)
Final Project
30 hours ⏳ (2 week × 15 h)
150 Total Workload Hours
6 ECTS Credits
Course Policies
Academic Integrity
All work submitted must be your own. Plagiarism, cheating, or any form of academic dishonesty will result in disciplinary action according to university policies. When in doubt about citation practices, consult the instructor.
Attendance Policy
Students are expected to adhere to the attendance requirements as outlined in the International University of Sarajevo Study Rules and Regulations. Excessive absences, whether excused or unexcused, may impact academic performance and eligibility for assessment. Mandatory sessions (e.g., labs, workshops) require attendance unless formally exempted. For detailed policies on absences, documentation, and penalties, please refer to the official university regulations.
Technology & AI Policy
Laptops/tablets may be used for note-taking only during lectures. Phones should be silenced and put away during all class sessions. Audio/video recording requires prior permission from the instructor.
Artificial Intelligence (AI) Usage: The use of AI tools (e.g., ChatGPT, Copilot, Gemini) varies by assessment component. Please refer to the AI usage indicator next to each assessment item in the Assessment Methods and Criteria section above. Submitting AI-generated content as your own work, where AI is not explicitly allowed, constitutes an academic integrity violation.
Communication Policy
All course-related communication should occur through official university channels (institutional email or SIS). Emails should include [BIO508] in the subject line.
Academic Quality Assurance Policy
Course Academic Quality Assurance is achieved through Semester Student Survey. At the end of each academic year, the institution of higher education is obliged to evaluate work of the academic staff, or the success of realization of the curricula.
Learning Tips
Be prepared to contribute thoughtfully during class discussions, labs, or collaborative work. Active participation deepens understanding and encourages critical thinking.
Complete assigned readings or prep materials before class. Take notes, highlight key ideas, and jot down questions. Aim to grasp core concepts and their applications—not just facts.
Use course frameworks or methodologies to analyze problems, case studies, or projects. Begin early to allow time for reflection and refinement. Seek feedback to improve your work.
Don’t hesitate to reach out when something is unclear. Use office hours, discussion boards, or peer networks to clarify concepts and stay on track.
Syllabus Last Updated on Feb 02, 2026 | International University of Sarajevo
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Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| BIO508 | Advanced Genetic Engineering | 3 | 0 | 6 | ||||||
| Prerequisite | None | It is a prerequisite to | - | |||||||
| Lecturer | Jasmin Šutković | Office Hours / Room / Phone | Tuesday: 9:00-12:00 Or any time via teams Thursday: 9:00-11:00 Or any time via teams |
|||||||
| jsutkovic@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | Introduce students to advanced topics in genetic engineering, including recent advancements in the field. | |||||||||
| Textbook | Research articles. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
| Teaching Methods | Lectures, presentations, video tutorials | |||||||||
| Teaching Method Delivery | Hybrid / blended | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction to the Course | TBD | ||||||||
| Week 2 | How to write article journal paper and search the databases! | TBD | ||||||||
| Week 3 | Assignment Presentations 1 | TBD | ||||||||
| Week 4 | Assignment Presentations 2 | TBD | ||||||||
| Week 5 | Assignment Presentations 3 | TBD | ||||||||
| Week 6 | Assignment Presentations 4 | TBD | ||||||||
| Week 7 | Assignment Presentations 5 | TBD | ||||||||
| Week 8 | MIDTERM PROJECT | - | ||||||||
| Week 9 | Assignment Presentations 6 | TBD | ||||||||
| Week 10 | Assignment Presentations 7 | TBD | ||||||||
| Week 11 | Assignment Presentations 8 | TBD | ||||||||
| Week 12 | Assignment Presentations 9 | TBD | ||||||||
| Week 13 | Assignment Presentations 10 | TBD | ||||||||
| Week 14 | Assignment Presentations 11 | TBD | ||||||||
| Week 15 | FINAL PROJECT | - | ||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Project | 1 | 40 | 1,2,3,4,5 | Consult Instructor | |
| Semester Evaluation Components | |||||
| Assignments | 2 | 30 | 1,2,3, | Consult Instructor | |
| Midterm project | 1 | 30 | 1,2,3,4, | Consult Instructor | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lectures | 3 | 15 | 45 | Asignment | 5 | 5 | 25 | |||
| Presentation | 4 | 5 | 20 | Home Study | 3 | 10 | 30 | |||
| Final Project | 15 | 2 | 30 | |||||||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 20/02/2026 | |||||||||