About this course
Successful completion of the level 1 course ‘Genomica’ (or ‘Systemsbiology’) and participation in the level 2 course ‘Data science and biology’ (or having followed a comparable course that provides experience in (unix) command line) is compulsory.
If you are a studentfrom outside the Utrecht University Biology Bachelor program and want to follow this course, please first consult with the course coordinator to discuss if you meet the entry requirements. For this course, basic knowledge in cell biology, genetics, and bioinformatics is compulsory, and we expect students to be familiar with the (unix) command line. After the course coordinator deems you eligible, you can register for the course by sending an e-mail to the study desk: [email@example.com](mailto:firstname.lastname@example.org" style="font-family:Arial,sans-serif; color:#bb7225; text-decoration:none) ,with the course coordinator in the Cc. Please note that courses at Biology are often oversubscribed and a place is not guaranteed, even if you meet the entry requirements. You will be notified by the study desk at the latest two weeks before the course starts if there is an opportunity to follow the course.
‘Genome Bioinformatics’ is a course in the study path ‘Theoretical Biology & Bioinformatics’. The course provides a good preparation for the Master program ‘Bioinformatics and Biocomplexity’ and is relevant for ‘Molecular and Cellular Life Sciences’ and ‘Environmental Biology’.
The language throughout the course, incl. the examination, is English.
Complex biological systems are formed by the interactions between molecules, cells, organisms, and their environment. The blueprints underlying these interactions are in principle encoded within the genome which itself is the result of 4 billion years of evolution. Biologists are nowadays able to rapidly generate large volumes of genomic data from individual species and populations, but also from complex environments. By contemporary bioinformatic research – as conducted in the Bioinformatics Group – this genomic data is turned into novel insights into the evolution, organization, regulation of genomes, and the emergence of biological function.
To be able to make novel biological discoveries using bioinformatic research, scientist must have a basic knowledge of patterns observable in prokaryotic and eukaryotic genome sequences and the evolutionary processes that generate or act on these patterns. Therefore, the aims of this course are three-fold: (i) students will acquire knowledge on evolutionary processes acting on genomes and their functional significance, (ii) learn how contemporary bioinformatics approaches have been used to identify these patterns in genomes, and (iii) acquire the required theoretical and practical skills to independently analyse and critically evaluate these patterns in large-scale datasets to make novel discoveries on the evolution and functioning of complex biological systems.
To achieve the overarching aims, the course has been divided into three parts:
In the first five weeks, the focus lies on the evolutionary processes operating on prokaryotic and eukaryotic genomes, and the bioinformatic approaches that have been and are currently used to identify evolutionary patterns and processes (how do these evolutionary signal look from a bioinformatic point of view). Next to an introduction into genome structure and evolution, students learn about evolutionary processes and patterns that can be observed in prokaryotic and eukaryotic genomes. Furthermore, students will be learning how bioinformatics approaches/tools work and how to critically interpret and reflect on their results.
The last four weeks places the focus on the research cycle (in bioinformatics). In small groups (2 or 3 students per group), students will perform a small research project in which they will apply their knowledge to analyses and critically reflect on large-scale bioinformatic analyses. Based on the topics of the research projects, students will write a MSc thesis proposal by which they will learn to formulate a research question/hypothesis and propose appropriate tools/approaches to address their research goals.
Lectures (with flipped-classroom component), computer practical (groups of 2 or 3), reviewing a science article, and writing and (peer-)reviewing a research proposal (individual) and a project report. Project results will be presented in a mini-symposium.
Grading - assessment
Active participation in practical, project, presentation assignments, and research proposal writing is mandatory. The final mark consists of a weighted average of: exam (60%), project (20%), and research proposal (20%). For each of the parts you have to get a grade of at least 5.0, and the weighted average of the entire course needs to be at least a 5.5
At the end of this course, students are expected to be able to…
know about major processes in prokaryotic and eukaryotic genome evolution, and their identifiable traces in biological data
apply and discuss the results of different state-of-the-art bioinformatic methodologies when studying evolution and function of complex biological systems, as derived from genomics data sampled over populations or conditions
critically reflect on results obtained from different bioinformatic methodologies by formulating hypotheses and expectations based on known processes and their traces in biological data
conduct a literature review, formulate a research question, devise scientific experiments, conduct experiments, and report on experiments (written/oral)
know about the scope of bioinformatic research, with a focus on research conducted at the Bioinformatics Group at Utrecht University
- Ability to work in teams: The research project as well as the presentations and reports are prepared in teams. Students have to distribute tasks and organize their work.
- Problem solving: Students produce data using bioinformatic approaches and have to use background information, literature resources, and bioinformatic methodologies to analyze and interpret data and describe and discuss their results in a written report and in a presentation.
- Technical/Analytical skills: Students learn to use bioinformatics methodologies to study (evolutionary) processes and patterns to reveal novel biological insights. Students will use programming languages and scripting to gather, analyse, and visualize large-scale biological data. Focus will be on the critical evaluation and reflections of results coming from large-scale bioinformatic methodologies.
- Writing/Presentation skills: Students will write a project report and present their project work, for which feedback is provided on form and content. Students will write a MSc research proposal where they demonstrate that they understand and apply the (bioinformatic) research circle, for which feedback on content and scientific language will be provided.
You must meet the following requirements
- Enrolled for one of the following degree programmes
- CreditsECTS 7.5
- Contact coordinator