Spring Selection 2017

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opens 10 Oct 2016
closes 15 Jan 2017

Computational Biology

From Cells to Biology in Cyberspace – The CompBio Track

Computational Biology • CompBio Track

The CompBio Track does research in theoretical and computational disciplines, like computer science, applied mathematics, computational engineering, and computational physics. Thanks to the close integration with the leading-edge biology and physics of the other tracks, this serves a double purpose: On the one hand, we advance computing and theory as inspired by the challenging systems and data of biology. On the other hand, we apply computational methods to help advance biology. This includes both the computational analysis of biological data (microscopy images, genome sequences, lineage trees, etc.) and computer simulations of biological systems and processes (computational biology).

Biological systems challenge the available computational methods, and the necessary foundations in computer science and mathematics are often missing. The CompBio Track hence performs fundamental research in computational and theoretical areas in order to develop the methodological foundations for future biology in tight integration with the experimental approaches of the other tracks.

Over the past decade, biological questions have become one of the major drivers of progress in computational science. At the same time, computational models and simulations are at the very heart of modern biology, enabling predictions of complex system behavior. Much research and progress in computer science and applied mathematics is however still required in order to cope with the intricacies and complexity of biological systems. The CompBio track drives these developments in an exciting, truly interdisciplinary program, and in tight integration with the biological applications.

Research Fields

  • Applied Mathematics
  • Bioinformatics
  • Computational Biology
  • Computational Genomics
  • Computational Science
  • Computer Science
  • Computer Vision/Image Processing
  • Parallel and High-Performance Computing
  • Scientific Computing
  • Software Engineering

Research Groups