The analysis of biological networks and the development of dynamical models to understand their function are at the core of systems biology. They have facilitated the move from the identification of molecular ‘parts lists’ for living organisms towards the integration of information from different ‘omics’-based approaches with our knowledge on the underlying biochemical mechanisms, in order to generate and test new hypotheses about how biological systems work.

Run jointly with EMBL-EBI, this course will provide participants with an introduction to network analysis and in-depth training in the main modelling approaches used in systems biology. The course will combine lectures, hands-on computational practical sessions and group activities, and there will be opportunity for discussion of current trends in the field.

Target audience: This course is aimed at PhD students and researchers who already have some experience of using systems-based modelling approaches to understand biological and biomedical problems. This is an advanced course, and participants are expected to have:

  • A working knowledge of using Linux commands, and experience of using a programming language (eg Python or Perl)
  • An undergraduate level knowledge of molecular and cellular biology

Learning outcomes
After this workshop, you should be able to:

  • Identify strengths and weaknesses in a variety of systems biology modelling approaches
  • Use a range of bioinformatics and modelling software to develop predictive and mechanistic models
  • Access, query and retrieve models from public repositories for systems biology
  • Identify an appropriate modelling approach for a given biological question and dataset

Feedback from the 2016 Course
"It was a really great course and I was able to learn a lot about different modelling approaches."
"It is really a nice course and I will definitely recommend others to come."
"This was all wonderful - thank you very much."
"Really great - thank you!"
"Very good."

Application Deadline:
Closed

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(or call us: +44 (0)1223 496910)


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