551-1201-00L Computational Methods in Genome and Sequence Analysis
| Semester | Autumn Semester 2023 |
| Lecturers | A. Wutz |
| Periodicity | yearly recurring course |
| Language of instruction | English |
| Comment | Number of participants limited to 7. The enrolment is done by the D-BIOL study administration. |
| Abstract | This course aims to provide students with a comprehensive overview of computational methods for sequence analysis and assist with developing skills for application of computational approaches by experimental scientists in the life sciences. | ||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Methods for analyzing animal genomes are increasingly becoming important for applications in human health and biotechnology suggesting that the experience will be useful to develop relevant expertise for a broad range of functions. Students will have the opportunity to advance their knowledge in programming by focusing on algorithms for genome and gene sequence analysis. A major goal of the course will be to lead the student to an independent and empowered attitude towards computational problems. For reaching this goal the students will work on an implementation of a solution for a set real-world problem in genome and sequence analysis under guided supervision. | ||||||||||||||||||||||||||||||||||||||||||
| Content | •Understanding the information in biological sequences and quantifying similarity •Introduction to algorithms for sequence comparison and searches •Implementation of sequence comparisons and searches in Python •Accessing data formats associated with genome sequence analysis tasks •Understanding the anatomy of a real world sequence analysis project •Applying tools for sequence alignment and estimating error rates •Ability to implement a solution to a problem in sequence analysis using Python •Accessing genome annotation and retrieving relevant information in Pandas •Application of Genomic intervals and arrays for sequence analysis with HTSeq The course will consist of a series of lectures, assignments for implementing elementary tasks in Python, project development and discussion workshops, and 3 and a half week of practical work implementing a Pythons script as a solution to a real world problem associated with sequence analysis. At the end of the course students will explain their solutions and demonstrate the functionality of their implementations, which will then be discussed and commented on by the group. It is expected that students will be able to apply the knowledge to improve on concrete problems. | ||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | - It is recommended to bring your own computer with a Python installation to the course - simple computers can be provided - Programming basics with Python | ||||||||||||||||||||||||||||||||||||||||||
Competencies |
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