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Instructor-led course

Provided by: Graduate School of Life Sciences


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Bioinformatics: Mathematical and computational modelling in biology
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Description

This course covers state-of-the-art tools and methods for system biology using biological data of different types. The participants will learn about the basis of modelling large-scale datasets as logic networks, as well as a more detailed approach using deterministic and stochastic modelling. At the end of the course the basis of three dimensional modelling of protein-protein interaction will be covered.

The course timetable can be found here.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here.

Target audience
  • The course is oriented to experimental researchers, post-doctoral and PhD students who want to gain a better understanding of the available tools and methodology used in system biology and to start modelling their own data.
  • Booking priority is given to people from Cambridge University and Collaborating Institutes
  • Individual Course fees are required only from External participants not from Collaborating Institutes
Topics covered
  • Logical modelling
  • Reverse engineering of large networks
  • Deterministic modelling
  • Stochastic processes and noise in biology
  • Spatial modelling
Aims

The aim of this course is to familiarise the students with the mathematical modelling of biological processes and to provide hands-on training using several of the most well known system biology software.

Format

Presentations, demonstrations and practicals

Duration

3

Frequency

Once a year


Events available