BIO646 Special Topics in Life Sciences 2
Syllabus | International University of Sarajevo - Last Update on Oct 10, 2025
Syllabus Quick Jump
Search and navigate to any syllabus instantly
Genetics and Bioengineering
Jasmin Šutković
Course Lecturer
Course Objectives
This course explores advanced topics in genetics and bioengineering, focusing on emerging trends, technologies, and computational tools. Students will engage with current research, learn to use bioinformatics tools, and critically analyze scientific literature. By the end of the course, each student will prepare and present a scientific paper on a topic of their choice, integrating genetic principles and bioinformatics approaches.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
- Genomes 4" by T.A. Brown - Bioinformatics and Functional Genomics" by Jonathan Pevsner - Online Tools: NCBI, Ensembl, UCSC Genome Browser, Galaxy, etc. - Journals: Nature Genetics, Genome Research, PLOS Genetics, etc.
Additional Literature
Lecture notes.Teaching Methods
Lectures
Case studies
Class discussions
Presentations
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction to Advanced Topics in Genetics and Bioengineering | |
| 2 | CRISPR and Gene Editing Technologies | |
| 3 | Epigenetics and Gene Regulation | |
| 4 | Synthetic Biology and Metabolic Engineering | |
| 5 | Personalized Medicine and Pharmacogenomics | |
| 6 | Genome-Wide Association Studies (GWAS) and Polygenic Risk Scores | |
| 7 | Single-Cell Genomics and Transcriptomics | |
| 8 | Midterm Presentations | |
| 9 | Structural Variants and Copy Number Variations (CNVs) | |
| 10 | Metagenomics and Microbiome Analysis | |
| 11 | Machine Learning in Genetics | |
| 12 | Scientific Writing and Peer Review | |
| 13 | Final Presentations | |
| 14 | Final Presentations | |
| 15 | Final review |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| BIO646.1 | Course | Tuesday 17:00 - 19:50 | B F2.1 | - | - |
Office Hours & Room
Assessment Methods and Criteria
Assessment Components
Final project paper
AI: Not AllowedAlignment with Learning Outcomes :
Weekly Assignments
AI: Not AllowedAlignment with Learning Outcomes :
Class perticipation
AI: Not AllowedAlignment with Learning Outcomes :
Midterm project
AI: Not AllowedAlignment with Learning Outcomes :
Final Presentation
AI: Not AllowedAlignment with Learning Outcomes :
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:
Assignments
8 hours ⏳ (2 week × 4 h)
Research study
63 hours ⏳ (9 week × 7 h)
Presentations
18 hours ⏳ (3 week × 6 h)
Project study
16 hours ⏳ (1 week × 16 h)
Lectures/Discussions
45 hours ⏳ (15 week × 3 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 [BIO646] 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 Oct 10, 2025 | International University of Sarajevo
Print Syllabus
Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| BIO646 | Special Topics in Life Sciences 2 | 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 | This course explores advanced topics in genetics and bioengineering, focusing on emerging trends, technologies, and computational tools. Students will engage with current research, learn to use bioinformatics tools, and critically analyze scientific literature. By the end of the course, each student will prepare and present a scientific paper on a topic of their choice, integrating genetic principles and bioinformatics approaches. | |||||||||
| Textbook | - Genomes 4" by T.A. Brown - Bioinformatics and Functional Genomics" by Jonathan Pevsner - Online Tools: NCBI, Ensembl, UCSC Genome Browser, Galaxy, etc. - Journals: Nature Genetics, Genome Research, PLOS Genetics, etc. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | Lectures, Case studies, Class discussions, Presentations | |||||||||
| Teaching Method Delivery | Hybrid / blended | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction to Advanced Topics in Genetics and Bioengineering | |||||||||
| Week 2 | CRISPR and Gene Editing Technologies | |||||||||
| Week 3 | Epigenetics and Gene Regulation | |||||||||
| Week 4 | Synthetic Biology and Metabolic Engineering | |||||||||
| Week 5 | Personalized Medicine and Pharmacogenomics | |||||||||
| Week 6 | Genome-Wide Association Studies (GWAS) and Polygenic Risk Scores | |||||||||
| Week 7 | Single-Cell Genomics and Transcriptomics | |||||||||
| Week 8 | Midterm Presentations | |||||||||
| Week 9 | Structural Variants and Copy Number Variations (CNVs) | |||||||||
| Week 10 | Metagenomics and Microbiome Analysis | |||||||||
| Week 11 | Machine Learning in Genetics | |||||||||
| Week 12 | Scientific Writing and Peer Review | |||||||||
| Week 13 | Final Presentations | |||||||||
| Week 14 | Final Presentations | |||||||||
| Week 15 | Final review | |||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final project paper | 1 | 40 | Not Allowed | ||
| Semester Evaluation Components | |||||
| Weekly Assignments | 1 | 20 | Not Allowed | ||
| Class perticipation | 1 | 10 | Not Allowed | ||
| Midterm project | 1 | 20 | Not Allowed | ||
| Final Presentation | 1 | 10 | Not Allowed | ||
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Assignments | 4 | 2 | 8 | Research study | 7 | 9 | 63 | |||
| Presentations | 6 | 3 | 18 | Project study | 16 | 1 | 16 | |||
| Lectures/Discussions | 3 | 15 | 45 | |||||||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 23/10/2025 | |||||||||