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Abstract
In this lecture, an introduction into main bioinformatics algorithms is provided. We will discuss both "classical" topics such as Hidden Markov Models, Markov chains, phylogenetic trees and "modern" approaches based on sophisticated (deep) learning models.
Objective
Students can understand the main algorithmic design principles for problems like sequence alignment, motif finding and phylogenetic inference. Further, students get an overview of modern machine learning methods and their applications to bio-medical problems.
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Bioinformatics Algorithms (University of Basel)
**Course at University of Basel**
|
No time listed | 3 h weekly |
Offered In
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Computational Biology and Bioinformatics Master (More information at: )
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Core Courses (The list of core courses is a closed list - no other courses can be added in this category. The assignment of the courses to the respective subcategory cannot be changed. Students must pass at least one course in each subcategory. A total of 40 ECTS must be acquired in the core course category, including the mandatory CBB seminar.)
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