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
Subject-specific Competencies
Concepts and Theories
fostered
Techniques and Technologies
assessed
Method-specific Competencies
Analytical Competencies
assessed
Decision-making
assessed
Media and Digital Technologies
assessed
Problem-solving
assessed
Project Management
assessed
Social Competencies
Communication
assessed
Cooperation and Teamwork
fostered
Negotiation
assessed
Personal Competencies
Creative Thinking
assessed
Critical Thinking
assessed
Self-awareness and Self-reflection
fostered
Self-direction and Self-management
assessed
Performance assessment
Performance assessment information (valid until the course unit is held again)
Repetition only possible after re-enrolling for the course unit.
Additional information on mode of examination
Students are obliged to be present throughout the block course. Cancellation: If you have to deregister from a course that has been assigned to you (just emergency reasons), please notify in written the course coordinator at least four weeks before the course starts, for courses in the 1st quarter, a cancellation period of one week applies. The study secretariat D-BIOL must also be informed (email CC to studies@biol.ethz.ch) so that the enrollment is deleted. Otherwise the course is considered as "failed".