BIO647 Modern Approaches to Genome Analysis
BIO647 Modern Approaches to Genome Analysis
Syllabus | International University of Sarajevo - Last Update on Mar 03, 2026
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Genetics and Bioengineering
Betul Akcesme
Course Lecturer
Course Objectives
The aim of this course is to introduce major areas of ongoing genome research to graduate students and to deepen their knowledge about the applications of these approaches especially in the field of medical sciences.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
Scientific Literature, Journal papers
Additional Literature
Related chapters of the defined textbooks https://www.hsls.pitt.edu/obrc/index.php?page=genomics http://www.fudan-pgx.org/premedkb/index.html#/homeTeaching Methods
Lecture presentations
Class discussions
Project design
Article discussions
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Biological Sequence Analysis | https://iris.who.int/bitstream/handle/10665/359560/9789240052857-eng.pdf?sequence=1 |
| 2 | Sequence analysis at the genomic scale: Genome browsers (Assignment I) | https://genome.ucsc.edu/ |
| 3 | Genome browsers, genome annotation ( SNPnexus) | https://www.snp-nexus.org/v4/ https://www.ncbi.nlm.nih.gov/clinvar/ |
| 4 | Variants (SNPs) and their importance in medicine (GWAS catalog) (Assignment II) | https://www.ebi.ac.uk/gwas/ http://www.fudan-pgx.org/premedkb/index.html#/home https://www.disgenet.org/ |
| 5 | Enrichment Analysis (g-profile, KEGG pathways) | https://biit.cs.ut.ee/gprofiler/gost https://www.genome.jp/kegg/kegg2.html |
| 6 | Project design (cancer or other diseses) (Assignment III) | https://portal.gdc.cancer.gov/ |
| 7 | Genomic sequence analysis (other tools and databases) | will be provided |
| 8 | Midterm (Project draft) | |
| 9 | Regulators and epigenetic approach to the mammalian genome | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9982057/ |
| 10 | Pharmacogenomics (Assignment IV) | https://humgenomics.biomedcentral.com/articles/10.1186/s40246-018-0157-3/ https://www.pharmgkb.org/page/cancerPgx / https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-017-0502-5 |
| 11 | Noncoding RNAs: importance in diagnosis & prognosis of diseases | https://www.mdpi.com/2073-4425/14/7/1429 https://www.nature.com/articles/s41573-021-00219-z |
| 12 | Genomics of bacteria and microbiota (Assignment V) | https://www.frontiersin.org/articles/10.3389/fgene.2018.00637/full |
| 13 | Genome sequencing Technologies (NGS platform) | will be provided |
| 14 | Project Evaluation before submission | |
| 15 | Presentation of the project |
Course Schedule (All Sections)
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Monday | 11:00 - 13:00 | A F1.34 | |
| Wednesday | 12:00 - 14:00 | A F1.34 |
Assessment Methods and Criteria
Assessment Components
Final Exam (project)
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5
Midterm exam (project draft)
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5
Assignments
AI: Not AllowedAlignment with Learning Outcomes :
Project 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:
Lecture hours
45 hours ⏳ (15 week × 3 h)
Projects
20 hours ⏳ (5 week × 4 h)
Home study
45 hours ⏳ (15 week × 3 h)
Midterm exam study
20 hours ⏳ (1 week × 20 h)
Final exam study
20 hours ⏳ (1 week × 20 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 [BIO647] 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 Mar 03, 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 | |||||||||
| BIO647 | Modern Approaches to Genome Analysis | 0 | 3 | 6 | ||||||
| Prerequisite | None | It is a prerequisite to | - | |||||||
| Lecturer | Betul Akcesme | Office Hours / Room / Phone | Monday: 11:00-13:00 Wednesday: 12:00-14:00 |
|||||||
| bakcesme@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | The aim of this course is to introduce major areas of ongoing genome research to graduate students and to deepen their knowledge about the applications of these approaches especially in the field of medical sciences. | |||||||||
| Textbook | Scientific Literature, Journal papers | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | Lecture presentations, class discussions, project design, article discussions | |||||||||
| Teaching Method Delivery | Hybrid / blended | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Biological Sequence Analysis | https://iris.who.int/bitstream/handle/10665/359560/9789240052857-eng.pdf?sequence=1 | ||||||||
| Week 2 | Sequence analysis at the genomic scale: Genome browsers (Assignment I) | https://genome.ucsc.edu/ | ||||||||
| Week 3 | Genome browsers, genome annotation ( SNPnexus) | https://www.snp-nexus.org/v4/ https://www.ncbi.nlm.nih.gov/clinvar/ | ||||||||
| Week 4 | Variants (SNPs) and their importance in medicine (GWAS catalog) (Assignment II) | https://www.ebi.ac.uk/gwas/ http://www.fudan-pgx.org/premedkb/index.html#/home https://www.disgenet.org/ | ||||||||
| Week 5 | Enrichment Analysis (g-profile, KEGG pathways) | https://biit.cs.ut.ee/gprofiler/gost https://www.genome.jp/kegg/kegg2.html | ||||||||
| Week 6 | Project design (cancer or other diseses) (Assignment III) | https://portal.gdc.cancer.gov/ | ||||||||
| Week 7 | Genomic sequence analysis (other tools and databases) | will be provided | ||||||||
| Week 8 | Midterm (Project draft) | |||||||||
| Week 9 | Regulators and epigenetic approach to the mammalian genome | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9982057/ | ||||||||
| Week 10 | Pharmacogenomics (Assignment IV) | https://humgenomics.biomedcentral.com/articles/10.1186/s40246-018-0157-3/ https://www.pharmgkb.org/page/cancerPgx / https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-017-0502-5 | ||||||||
| Week 11 | Noncoding RNAs: importance in diagnosis & prognosis of diseases | https://www.mdpi.com/2073-4425/14/7/1429 https://www.nature.com/articles/s41573-021-00219-z | ||||||||
| Week 12 | Genomics of bacteria and microbiota (Assignment V) | https://www.frontiersin.org/articles/10.3389/fgene.2018.00637/full | ||||||||
| Week 13 | Genome sequencing Technologies (NGS platform) | will be provided | ||||||||
| Week 14 | Project Evaluation before submission | |||||||||
| Week 15 | Presentation of the project | |||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Exam (project) | 1 | 40 | 1,2,3,4,5 | Not Allowed | |
| Semester Evaluation Components | |||||
| Midterm exam (project draft) | 1 | 30 | 1, 2, 3, 4, 5 | Not Allowed | |
| Assignments | 5 | 25 | Not Allowed | ||
| Project Presentation | 1 | 5 | Not Allowed | ||
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lecture hours | 3 | 15 | 45 | Projects | 4 | 5 | 20 | |||
| Home study | 3 | 15 | 45 | Midterm exam study | 20 | 1 | 20 | |||
| Final exam study | 20 | 1 | 20 | |||||||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 27/03/2026 | |||||||||