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Course content

Ecologists and evolutionary biologists now routinely use next-generation DNA sequencing in their research, and graduates who are skilled in both genome analysis as well as ecology and evolution are rare. Genome-enabled approaches are helping rapidly to advance our understanding of the dynamic relationship between genotype, phenotype and the environment.

Our programme will give you cross-disciplinary skills in a rare combination of areas of expertise, from bioinformatics and evolutionary inference to computational biology and fieldwork.

You will be taught by researchers who apply genomic methods to a wide range of issues in ecology and evolution, from bat food-webs and genome evolution to microbial biodiversity in natural and engineered ecosystems. For example, Professor Steve Rossiter carries out world-leading research on bat genome evolution; Dr Yannick Wurm has discovered a social chromosome in fire-ants; and Dr China Hanson is using genetic methods to study microbial biogeography. This means that teaching on our programme is informed by the latest developments in this field, and your individual research project can be at the forefront of current scientific discovery. 

You will conduct your own substantive six-month research project, which may be jointly supervised by contacts from related institutes or within industry. You will also take part in a field course in Borneo - see photos from a recent trip on Flickr - giving you the opportunity to develop first hand experience of theory in action.

Programme highlights

  • Work with leading researchers in environmental genomics - learn more on the Evolution and Genetics research group page 
  • Two-week tropical ecology field trip (currently to Borneo)
  • Strong foundation for careers in consultancy, environmental policy and management or research
  • Strong foundation for PhD training in any area of genomics, ecology or evolution

Research and teaching

By choosing to study at a Russell Group university you will have access to excellent teaching and top class research. You can find out more about our research interests and view recent publications on the School of Biological and Chemical Science's Evolution and Genetics group page.

Structure

This MSc programme combines taught modules with individual and collaborative research projects. You will apply the knowledge and techniques from your taught modules in a practical setting and may be able to publish your project findings.

If you have any questions about the content or structure, contact the programme director Dr Christophe Eizaguirre.

Taught modules

  • Genome Bioinformatics: Covers the essential aspects of next generation sequence (NGS) analysis, including genome assembly, variant calling and transcriptomics. Also covers essential computer skills needed for bioinformatics, such as Linux and using our high performance computing cluster.
  • Coding for scientists: Assuming no prior programming knowledge, teaches you how to program in Python, using biological examples throughout. Python is one of the most popular languages in the bioinformatics community, and understanding Python provides the perfect foundation for learning other languages such as Perl, Ruby and Java.
  • Statistics and bioinformatics: Covers core statistics methods, within the R statistical computing environment. R has become the de facto environment for downstream data analysis and visualisation in biology, thanks to the hundreds of freely available R packages that allow biological data analysis solutions to be created quickly and reliably.
  • Post-genomics bioinformatics: Introduces techniques that have developed as a consequence of developments in genomics (i.e. transcriptomics, proteomics, metabolomics, structural biology and systems biology) with particular emphasis on the data analysis aspects. Practicals cover the popular Galaxy framework, advanced R, and machine learning.
  • Research frontiers in evolutionary biology: Exploring the frontiers of research in evolutionary biology. Topics covered will include: incongruence in phylogenetic trees, neutral versus selective forces in evolution, the origin of angiosperms, the origin of new genes, the evolution of sociality, the significance of whole genome duplication and hybridisation. Current methods being used to tackle these areas will be taught, with an emphasis on DNA sequence analysis and bioinformatics.

Research modules

  • Evolutionary/Ecological Analysis/Software Group Project module: Students are organised into small teams (3-4 members per team). Each team is given the same genomic or transcriptomic data set that must be analysed by the end of the module. Each team must design an appropriate analysis pipeline, with specific tasks assigned to individual team members. This module serves as a simulation of a real data analysis environment, providing invaluable experience for future employability.
  • Individual Research Project (50 per cent of the programme)

Visit the MSc Ecological and Evolutionary Genomics page on the Queen Mary University of London website for more details!

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