In bioinformatics the data are typically multidimensional and contain noise as well as technical and biological variability. Furthermore the underlining biological mechanisms to be analysed are in general unknown and have a complex nature. Therefore models must be learned from the data. This makes bioinformatics an interesting and challenging application area for machine learning. In this course, the student will study issues and selected topics in bioinformatics and will learn to develop and apply machine learning approaches and algorithms for tackling these problems.
Wout Megchelenbrink
Material
Slides, research papers and surveys will be available during the course.
Based on one practical project and exercises.
See BB.