Found 8 relevant results in 1.76s where lecturer="Niko Beerenwinkel"

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636-1005-AAL 2020S , 2020W , 2021S , 2021W , 2022S , 2022W , 2023S 5 Credits MSC D-BSSE , D-INFK

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636-0704-00L 2020S , 2020W , 2021S , 2021W , 2022S , 2022W , 2023S , 2023W , 2024S , 2024W , 2025S , 2025W , 2026S , 2026W 2 Credits MSC D-BSSE , D-INFK

Computational Biology und Bioinformatik analysieren lebende Systeme mit Methoden der Informatik. Das Seminar kombiniert Präsentationen von Studierenden und Forschenden, um das sich schnell entwickelnde Gebiet aus der Informatikperspektive zu skizzieren. Themenbereiche sind Sequenzanalyse, Proteomics, Optimierung und Bio-inspired computing, Systemmodellierung, -simulation und -analyse.

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636-0301-00L 2020S , 2020W , 2021S , 2021W , 2022W 2 Credits DR D-BSSE

This seminar will feature invited lectures about recent advances and developments in systems biology, including topics from biology, bioengineering, and computational biology.

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529-0990-00L 2008W 2 Credits MSC D-CHAB

This seminar will feature invited lectures about recent advances and developments in systems biology, including topics from biology, bioengineering, and computational biology.

636-0009-00L 2020W , 2021W , 2022W , 2023W , 2024W , 2025W , 2026W 6 Credits DR , MSC D-INFK , D-MATH , D-BIOL , D-BSSE

Evolutionary dynamics is concerned with the mathematical principles according to which life has evolved. This course offers an introduction to mathematical modeling of evolution, including deterministic and stochastic models, with an emphasis on tumor evolution.

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262-0001-00L 2008W 5 Credits MSC D-BSSE , D-INFK , D-CHAB

The goal of this course is to understand and to appreciate mathematical models and computational methods that provide insight into the evolutionary process.

636-0702-00L 2020S , 2021S , 2022S , 2023S , 2024S , 2025S , 2026S 6 Credits BSC , DR , MSC , NDS D-BSSE , D-INFK , D-MATH , D-PHYS , D-BIOL , D-ITET

The course offers an introduction to graphical models and their application to complex biological systems. Graphical models combine a statistical methodology with efficient algorithms for inference in settings of high dimension and uncertainty. The unifying graphical model framework is developed and used to examine several classical and topical computational biology methods.

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636-0101-00L 2020S , 2021S , 2022S , 2022W , 2023W , 2024W , 2025W , 2026W 4 Credits DR , MSC D-INFK , D-BSSE

This course is an introduction to the wide field of Genomics. It addresses how fundamental questions in biological systems are studied using methods in genomics and how the resulting data is analysed to make quantitative interpretations of biological phenomena.

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