Applied Systems Biology

There is great demand for interdisciplinary scientists who are capable of generating, handling, analysing and interpreting the high-throughput data obtained from current biological research in academia and industry. Being able to effectively contribute and communicate within a skills-diverse research team will soon be considered an essential employee skill.

These modules (which you can start at any point in the year) aim to provide bioscientists with relevant and practical computing skills appropriate for an interdisciplinary research career. The modules are supported by Unilever, which has contributed to their overall design and delivery.

Taken collectively, our suite will significantly boost your interdisciplinary skills and knowledge in computationally based approaches in biosciences.  However, there is the option to study modules individually based around your specific learning needs.

All material will be accessible during each-15 week course, ensuring that the pace and time commitment of the module is entirely under each delegate’s control. This will allow members of a workforce to participate without affecting their performance at work.

Integrative interpretation of large-scale data 

Start date: On-going  (applicants can apply year round) 

Cost: £1,250

The module provides conceptual understanding and hands on experience of Bioinformatic tools for accessing and interpreting high-throughput -omics data.

More information


Systems modelling and network analysis

Start date: On-going  (applicants can apply year round)

Cost: £1,250

This module provides comprehensive knowledge of the main, current techniques used in computational Systems Biology simulations. 

 More information


Quantitative data analysis

Start date:  On-going (applicants can apply year round)

Cost: £1,250

This module is designed to give supported, hands on experience of computational programming and data analysis within the statistical programming environment R, including the processing and analysis of ‘-omics’ data.

More information

Apply Now

Supported by


Programme Leader

Emma Laing






Dr Emma Laing

Senior lecturer in Bioinformatics, Head of Bioinformactics 

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