Credits: 5

Schedule: 11.09.2017 - 08.12.2017

Teaching Period (valid 01.08.2018-31.07.2020): 

IV-V (Spring 2019), lectured every other year (not lectured in the academic year 2019-2020), alternating with CS-E5890

Learning Outcomes (valid 01.08.2018-31.07.2020): 

The students will learn how machine learning used in different bioinformatics applications and get hands-on knowledge on the use of machine learning in project work.
Students will get training on scientific work, presenting research orally and in written from and giving feedback on other students’s work.

Content (valid 01.08.2018-31.07.2020): 

Machine learning is one of the cornerstone technologies in bioinformatics, used in numerous tools and applications. This course probes the state of the art in selected machine learning problems and the associated methods in bioinformatics, through introductory lectures and project work. The introductory lectures present and overview of the problem domain, and the set of methods to be applied in the projects. Varying applications such as regulatory genomics, protein function and interactions, drug bioactivity, metabolomics, and genome-wide association analysis are offered as project topics.

Assessment Methods and Criteria (valid 01.08.2018-31.07.2020): 

To be specified in MyCourses at the start of the course.

Workload (valid 01.08.2018-31.07.2020): 

Learning diaries, poster presentation and written report.

Study Material (valid 01.08.2018-31.07.2020): 

Collection of articles.

Substitutes for Courses (valid 01.08.2018-31.07.2020): 

T-61.6080 Special Course in Bioinformatics II, CS-E4860 Special Course in Bioinformatics.

Grading Scale (valid 01.08.2018-31.07.2020): 

0-5.

Description