Computational biology involves the application of computers and computer science to the understanding and modelling of biological structures and processes.
Computational biology entails the use of computational methods (e.g., algorithms) for the representation and simulation of biological systems, as well as for the interpretation of experimental data, often on a very large scale. This stream also focusses on modelling biological processes using a mixture of mathematical and computer models.
Why study computational biology at UCL?
UCL is an international leader in computational biology research and has many collaborations between the biological sciences, and mathematics, statistics and computer science. Students coming to UCL will have access to the expertise found within the UCL Centre for Computational Biology.
ALL areas of the biosciences are seeking early career scientists with strong quantitative (computing, mathematical, statistical) skills. Students graduating through the Computational Biology stream will be very competitive for PhD places as well as careers in the private sector computing and bioinformatic areas.
Topics covered at UCL
Research covers a wide range of biological problems including theoretical and statistical ecology (e.g. Richard Pearson; David Murrell; Wenying Shou), computational and statistical genetics (e.g. Richard Mott; Garrett Hellenthal); computational genomics (Maria Secrier; Aida Andrés); evolutionary genetics (Andrew Pomiankowski; Max Reuter; Ziheng Yang); systems biology (Francois Balloux; Chris Barnes; Wenying Shou); and quantitive biology (Wenying Shou).
Example recent project titles
- High dimensional predictive modeling of acute cognitive dysfunction
- The evolution of niche with and without mutualism
- Analysing mitochondrial segregation in fission yeast
- Artificial selection of whole microbial communities
Statistical causal inference from observational time series data
Specific applicant information
The programme is seeking applications from students who are keen to further their skills in computational biology across any of the topics covered above. Applicants should be able to demonstrate strong skills in mathematics, statistics and/or computer programming and as well as a strong desire to apply them to key questions in biology. Interested students can contact the stream tutor Ziheng Hang by emailing firstname.lastname@example.org or the overall programme lead David Murrell email@example.com
Computational Biology taught module
The student will choose a taught module after discussion with the project supervisor, as the taught module may be related to the research project. Possible options include the following:
- Advanced Computational Biology
- Computational and Systems Biology
- Molecular Evolution
- Data Science Methods in Biology
Please Note: There may be access to modules other than those provided in the following lists. However, all optional modules must have the approval of the subject stream tutor. Some modules may be appropriate for more than one subject stream. You can view further information about the modules in the Module Catalogue.