Vorlesung: Visual Computing in the Life Sciences


  • Dozent(en):
  • Beginn: 09.04.2018
  • Zeiten: Mon and Thu 10:30-12:00 INF/B-IT U.105
  • Studiengang: B-IT Master Life Science Informatics
  • Aufwand: 4 SWS / 6 CP
  • Prüfungen: First: Thu Jul 19, 10-12 Second: Thu Aug 23, 10-12



externYour feedback on our lecture is appreciated!

In recent years, methods from visual computing have gained significant and increasing importance within bioinformatics and the life sciences. This is due to two main factors:

  1. Given ever-increasing volumes of sequencing data, suitable analysis and understanding of multi-dimensional data replaces data generation as the bottleneck in gaining biological insight. Graphical representations can augment our ability to reason about such data, and integrating them with automated data analysis allows scientists to better understand and steer data processing.
  2. The life sciences make increasing use of digital images, primarily from microscopy and Magnetic Resonance Imaging (MRI). Performing quantitative analysis of such data requires suitable methods for image processing, including image registration and segmentation.

The range of available tools is as diverse as the research questions and methods in the life sciences. Our class focuses on important basic principles of human perception, techniques for visualization of multi-dimensional data and graphs, image segmentation, registration, and statistical analysis, and provides some specific example applications within bioinformatics.

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Übung 1: Data-manipulation
Übungsblatt  (PDF-Dokument, 168 KB)
Übung 2: Scatter-Plots-Dimensionality-Reduction
Übungsblatt  (PDF-Dokument, 129 KB)
Übung 3: tSNE-Graph-Visualization
Übungsblatt  (PDF-Dokument, 187 KB)
Übung 4: SpectralClustering-GMM
Übungsblatt  (PDF-Dokument, 211 KB)
Übung 5: ImageFiltering-MRFs
Übungsblatt  (PDF-Dokument, 317 KB)
Übung 6: DeepLearning
Übungsblatt  (PDF-Dokument, 127 KB)