Msc in Bioinformatics and Computational Biology

Key Points

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Bioinformatics is a rapidly growing field at the intersection of biology, mathematics and computer science. It seeks to create, advance, and apply computer/software-based solutions to solve formal and practical problems arising from the management and analysis of very large biological datasets. Applications include genome sequence analysis, such as the human genome, the human microbiome, analysis of genetic variation within populations, and analysis of gene expression patterns.

The master’s program will train participants to an advanced level in bioinformatics theory and applications. Graduates of the program:

They will have a solid background in the theory behind bioinformatics methods and tools so that they can critically evaluate bioinformatics research.
They will be able to use existing bioinformatics methods and tools and quickly learn to apply new methods and tools.
They will be able to organize, process and analyze large datasets generated by systems biology and genomics approaches.
They will be able to program and create scripts to parse various biological data formats within a command line computing environment.
Understand the role of modeling and simulation of biological systems.
They will have an in-depth knowledge of the aspect of bioinformatics in which they conducted their three-month research project (as part of the master’s program). This experience will prepare them for a future research career in the field of bioinformatics.

Program structure

The master’s programme has four different streams: for graduates in biology, mathematics, statistics and computer science, respectively.

Students are required to complete 12 modules and undertake a research project. Each module consists of approximately 20 one-hour lectures (approximately two lectures per week during an academic term), as well as approximately 10 hours of practicals or tutorials (approximately one one one-hour practicum or tutorial per week during an academic term), although the exact number of lectures, practicals and tutorials varies between individual modules.

Current for graduates in Biological Sciences

Mathematical Modeling for Biological and Environmental Sciences (5 credits)
Open Source Infrastructure for Modeling and Big Data (5 credits)
Introduction to relational databases (5 credits)
Data Mining (5 credits)
Programming for Bioscientists I (5 credits)
Programming for Bioscientists II (5 credits)
Computational Systems Biology (5 credits)
Genomic Data Analysis (5 credits)
Thesis in Bioinformatics and Computational Biology (30 credits)
Discrete Mathematics (5 credits)
Data Analysis I (5 credits)
Data Analysis II (5 credits)
Introduction to Probability and Statistics (5 credits)

Computer Science Graduate Stream

Introduction to Probability and Statistics (5 credits)
Molecular Biology (5 credits)
Biomolecules (5 credits)
Cells, biomolecules, genetics and evolution (5 credits)
Data Mining (5 credits)
Programming for Bioscientists I (5 credits)
Programming for Bioscientists II (5 credits)
Computational Systems Biology (5 credits)
Genomic Data Analysis (5 credits)
Dissertation in Bioinformatics and Computational Biology (30 credits)
Discrete Mathematics (5 credits)
Data Analysis I (5 credits)
Data Analysis II (5 credits)

Current for Mathematics graduates

Choice of: Data Analysis I (5 credits) o Data Analysis II (5 credits)
Mathematical Modeling for Biological and Environmental Sciences (5 credits)
Molecular Biology (5 credits)
Biomolecules (5 credits)
Cells, biomolecules, genetics and evolution (5 credits)
Open Source Infrastructure for Modeling and Big Data (5 credits)
Data Mining (5 credits)
Programming for Bioscientists I (5 credits)
Programming for Bioscientists II (5 credits)
Introduction to relational databases (5 credits)
Computational Systems Biology (5 credits)
Genomic Data Analysis (5 credits)
Dissertation in Bioinformatics and Computational Biology (30 credits)

Current for graduates in Statistics

Mathematical Modeling for Biological and Environmental Sciences (5 credits)
Molecular Biology (5 credits)
Biomolecules (5 credits)
Cells, biomolecules, genetics and evolution (5 credits)
Open Source Infrastructure for Modeling and Big Data (5 credits)
Introduction to relational databases (5 credits)
Data Mining (5 credits)
Programming for Bioscientists I (5 credits)
Programming for Bioscientists II (5 credits)
Computational Systems Biology (5 credits)
Genomic Data Analysis (5 credits)
Dissertation in Bioinformatics and Computational Biology (30 credits)
Discrete Mathematics (5 credits)

Career options

Working in the field of bioinformatics is a challenging and fulfilling job, often involving problem solving, programming, statistical analysis of large data sets, and mathematical modeling of biological phenomena. A bioinformatician is likely to work on many different biological questions and types of data sets, which makes this an interesting and exciting field to work in.

The daily work of a bioinformatician may involve the study of different fascinating and important biological questions, such as:

How many genes are there in the human genome and can we identify them all?
What differences exist in the DNA of different people and how does that affect their health, appearance, and behavior?
Is it possible to create a computer program to analyze the DNA sequences of 1000 different individual humans and reconstruct their genetic history?
What are the differences between cancer cells and healthy cells?
How do new drug-resistant strains of malaria evolve from existing strains and can we predict which strains will emerge in the future?
What bacteria are present in different environments, such as different parts of the human body in people of different ages, populations, and health?
How are different groups of animals (e.g., humans, flies, jellyfish, earthworms, etc.) related to each other, and when and where did they evolve from a common ancestor?
And many other interesting and important questions

Admission requirements

Participants in the programme must hold an honours degree, or equivalent qualification, in a discipline with a significant element of mathematics, statistics, engineering, computer science or biology, with a minimum of a second class 1 honours degree.
In the case of international candidates, the foreign equivalent is required. In addition, a degree officially translated into English will be required.
IELTS 6.5, with no less than 6 in any component (or its internationally recognised equivalent).

No prior knowledge of computer programming or bioinformatics is required to take the course. All necessary computer skills will be taught as part of the program