BIO405 Biological Data Analysis with Python
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| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| BIO405 | Biological Data Analysis with Python | 1 | 2 | 6 | Tuesday 15:00-17:50 | |||||
| Prerequisite | ENS213 / CS103 | It is a prerequisite to | None |
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| Lecturer | Muhamed Adilović | Office Hours / Room / Phone | Monday: 9:00-12:00 Friday: 9:00-11:00 |
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| madilovic@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | This course aims to teach students how to look for, process, analyze, and represent biological data using Python programming language. | |||||||||
| Textbook | Python Programming for Biology: Bioinformatics and Beyond; Cambridge University Press; 1st edition | |||||||||
| Additional Literature |
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| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
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| Teaching Methods | Lecture presentations, coding demonstrations, problem solving, and class discussions. | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction | Ch. 1 | ||||||||
| Week 2 | Python and Biology Basics | Ch. 2 | ||||||||
| Week 3 | More Python, GENCODE, RefSeq | Ch. 3 | ||||||||
| Week 4 | Data Formats, Functional Programming, Genome Browsers | Ch. 4-5 | ||||||||
| Week 5 | Biopython, More Functional Programming, UniProt | Ch. 5 | ||||||||
| Week 6 | Sequence Alignment and Error Handling | Ch. 11-13 | ||||||||
| Week 7 | Pfam, Regex, NumPy | Ch. 9 | ||||||||
| Week 8 | Midterm | |||||||||
| Week 9 | Pandas | Ch 6 | ||||||||
| Week 10 | Visualization, Gene Expression | Ch 16 | ||||||||
| Week 11 | ClinVar, OOP, Advanced Pandas | Ch 7-8 | ||||||||
| Week 12 | Statistics | Ch 22 | ||||||||
| Week 13 | Statistics Continued | Ch 23 | ||||||||
| Week 14 | Human Genetic Variation, Modules, Multivariate Analysis | Ch 14 | ||||||||
| Week 15 | Review for the Final Exam | |||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs |
| Final Exam | 1 | 40 | 1,2,3,4,5 | |
| Semester Evaluation Components | ||||
| Midterm exam | 1 | 24 | 1,2,3,4,5 | |
| Projects | 6 | 36 | 1,2,3,4,5 | |
| *** 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: 02/11/2022 | |||||||||