Msc ecological and evolutionary genomics biological sciences

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

• Genome Bioinformatics: This module provides an introduction to bioinformatics, focusing specifically on the analysis of DNA sequence data. Lectures cover the bioinformatics methods, algorithms and resources used for tasks such as sequence assembly, gene finding and genome annotation, phylogenetics, analysis of genomic variance among populations, genome wide association studies and prediction of gene structure and function. Practical exercises are used to gain experience with relevant existing bioinformatics tools, data formats and databases.
• Coding for Scientists: This module provides a hands-on introduction to computer programming (popularly known as coding) using scripting languages popular in the field. The focus is on producing robust software for repeatable data-centric scientific work. Key programming concepts are introduced, and these concepts are then brought together in scientifically relevant applications to analyse data, interact with a database and create dynamic web content. Good coding practice, such as the importance of documentation and version control, is emphasised throughout.
• Statistics and Bioinformatics: This module is focussed on teaching data analysis using the statistical programming language R. The module covers the basics of using R; drawing publication-standard graphs with R; experimental design; exploratory data analysis; the fundamentals of statistical testing including t-tests and chi-square tests; ANOVA and Regression; fitting and interpreting general linear models; the basics of bioinformatic analysis in R. The module is taught with a mix of theory and practice, with a typical day including roughly two hours of theory instruction in the morning followed by a practical session in the afternoon, often involving hands-on analysis of real experimental data sets.
• Post-genomic Bioinformatics: This module provides an introduction to bioinformatics, focusing specifically on the management and analysis of data produced by so-called post-genomic methods such as transcriptomics, proteomics and metabolomics. Lectures cover the bioinformatics methods, algorithms and resources used for tasks such as the identification and quantitation of transcripts, proteins and metabolites, and analysis of the interactions between these key biological molecules. Practical exercises are used to gain experience with bioinformatics tools, data formats and databases that have been developed for this field.
• Research Frontiers in Evolutionary Biology: This module will explore 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 method being used to tackle these areas will be taught, with an emphasis on DNA sequence analysis and bioinformatics. This module aims to inspire students to seek a career in scientific research, and equip them to choose areas of research that are of current interest. Whereas undergraduate degrees commonly focus on what we know, this Master's course will shift the focus onto what we don't know. Students will explore the current frontiers of knowledge, and the questions that currently lack answers, or whose answers are currently debated. Students will learn to ask relevant questions themselves, and design approaches to seeking answers to those questions.
• Ecology and Evolutionary Biology Field Course - The module comprises a residential field course lasting approximately 12 days, designed to allow students to develop their field skills in situ. Teaching will comprise a combination of lectures, demonstrations and practical assignments. These will span topics in taxonomy, ecology, biogeography, conservation and evolution. Students will also undertake their own mini-project. This field-based module will include coverage of ecological processes in tropical rainforests (decomposition, pollination and seed dispersal), rainforest structure and defining characteristics (including the importance of rainforests as centres of biodiversity), and anthropogenic factors affecting rainforests (including disturbance, forest fragmentation and agriculture).

• 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)

Find out more about this programme in our Ecological and Evolutionary Genomics student handbook.