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Computational Biology Group

The UEA Computational Biology Group  promotes an integrative philosophy to computational biology, with areas of research spanning the biological hierarchy from genome through to ecosystem.

In addition to carrying out high quality research with international and national partners, group develops  computational biology with scientists across the Norwich Research Park (NRP). NRP represents Europe's largest and most successful single site concentration of research and development in the areas of plants, food, diet, health, the environment, and information systems.  

Members of the group collaborate collaborate closely with computational biologists and other scientists  from NRP institutions such as the School of Biological Sciences, the School of Environmental Sciences, the John Innes Centre, The Earlham Institute, Quadram Institute and the Sainsbury Laboratory.

If you are interested in studying for a research degree in Computing Science, visit Research Degrees for more information.

Research Themes

Publications, Projects and Software

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Publications

As a group, we are highly cited, have published in many high-impact journals and presented at prestigious, international conferences.

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Projects

Members of the Computational Biology Group are involved in various computational biology research projects, some of which are listed here.

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Software

Members of the Computational Biology Group are involved in the development of various computational biology software packages, some of which are listed here.

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Events

Members of the Computational Biology Group both attend and help organise international and local events. Here are the more recent events.

New Directions in Experimental Mathematics

Novel Mathematical Paradigm for Phylogenomics (25w5333)

Midsummer Phylogenomics 2025 (PDF, 349KB)

Funding

The computational biology group pursues a wide range of projects with funding from research councils, societies, governments and industry. This diverse financial support highlights the group's commitment to advancing research, innovation, and addressing real-world challenges.

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Computational Biology