The final grade is based on collaboration and performance,a lab journal of week 1, a written report on the project of week 2 of the practical course, and one or two short oral presentations.

The focus of this practical course is placed on the design and practical implementation of effective visualizations of biological data. Students will learn guidelines and use of methods for visualizing data. This hands-on course uses real-world data; the focus is on the entire process of designing and implementing effective visualization and visual analysis of biological data, from data and task analysis to selecting appropriate visualization methods and designing interactive visual analytics applications; different methods are compared in terms of their effectiveness for analysis and communication. Topics of the first weekinclude color and perception, bioinformatics methods for data preprocessing, visualization techniques for biological data, for example multidimensional and temporal data, networks and structures, and the basics of visual analytics and visual storytelling. During the second week students work on a self-chosen small research project that combines bioinformatics with visualisation methods.

Students gain practical experience in designing and programming interactive visualizations for the analysis of biological data. They are able to use libraries and frameworks and acquire or expand their knowledge of JavaScript (mainly D3) and Python. By working in groups, students acquire teamwork and collaboration skills and learn project organization and presentation techniques. Students know the strengths and weaknesses as well as the limitations of different visualization methods and can describe and evaluate these methods.

Will be provided at the beginning of the course, if necessary.