Master of Bioinformatics (Leuven)

What is the Master of Bioinformatics all about?

Bioinformaticians are distinguished by their ability to formulate biologically relevant questions, design and implement the appropriate solution by managing and analyzing high-throughput molecular biological and sequence data, and interpret the obtained results.

Programme

This interdisciplinary two-year programme focuses on acquiring:

• basic background knowledge in diverse disciplines belonging to the field of bioinformatics, including statistics, molecular biology, and computer science;
• expert knowledge in the field of bioinformatics;
• programming skills;
• engineering skills.

The 120-credit programme consists of a reorientation package (one semester), a common package (two semesters) and a thesis.

The Master of Bioinformatics is embedded in a strong bioinformatics research community in KU Leuven, who monthly meet at the Bioinformatics Interest Group. Bioinformatics research groups are spread over the Arenberg and Gasthuisberg campus and are located in the research departments of Microbial and Molecular Systems (M2S), Electrical Engineering (ESAT), Human Genetics, Microbiology and Immunology (REGA), Cellular and Molecular Medicine, Chemistry and Biology. Several of these bioinformatics research groups are also associated with the Flemish Institute for Biotechnology (VIB).

International

Are you looking to broaden your horizons? There are ample opportunities to conduct part of your master's thesis research at various partner institutions abroad. In addition, European residents can undertake their master's thesis research at a European or another partner university within the framework of the Erasmus+ programme. The Faculty also welcomes initiatives of students who want to do a work placement in a company or organization abroad, as well as exchange programmes with partner universities.

More information: www.biw.kuleuven.be/english/index.aspx

This is an initial Master's programme and can be followed on a full-time or part-time basis.

Objectives

Learning outcomes Master of Bioinformatics

The student

1. Possesses a broad knowledge of the principles of genetics, biochemistry and molecular and cellular biology that underlie the model systems, the experimental techniques, and the generation of data that are analyzed and modeled in bioinformatics.
2. Possesses a broad knowledge of the basic mathematical disciplines (linear algebra, calculus, dynamical systems) that underlie mathematical and statistical modeling in bioinformatics.
3. Masters the concepts and techniques from information technology (database management, structured and object-oriented programming, semantic web technology) for the management and analysis of large amounts of complex and distributed biological and biomedical data.
4. Masters the concepts and techniques from machine learning and frequentist and Bayesian statistics that are used to analyze and model complex omics data.
5. Has acquired knowledge of the core methods of computational biology (such as sequence analysis, phylogenetic analysis, quantitative genetics, protein modeling, array analysis).
6. Has advanced interdisciplinary skills to communicate with experts in life sciences, applied mathematics, statistics, and computer science to formalize complex biological problems into appropriate data management and data analysis strategies.
7. Can - in collaboration with these experts - design complex omics experiments and analyze them independently.
8. Can independently collect and manage data from specialized literature and public databases and critically analyze and interpret this data to solve complex research questions, as well as develop tools to support these processes.
9. Investigates and understands interaction with other relevant science domains and integrate them within the context of more advanced ideas and practical applications and problem-solving.
10. Demonstrates critical consideration of and reflection on known and new theories, models or interpretation within the specialty; and can efficiently adapt to the rapid evolution the life sciences, and especially in omics techniques, by quickly learning or developing new analysis strategies and incorporating them into the learned competencies.
11. Presents personal research, thoughts, ideas, and opinions of proposals within professional activities in a suitable way, both written and orally, to peers and to a general public.
12. Develop and execute original scientific research and/or apply innovative ideas to research units.
13. Understands ethical, social and scientific integrity issues and responsibilities and is able to analyze the local and global impact of bioinformatics and genomics on individuals, organizations, and society.
    
    Major Engineering
14. Has a broad theoretical knowledge of methodology in computer science and can apply this knowledge to design, implement and evaluate a computer-based system, process, component or programme to solve technical bioinformatics problems.
    
    Major Bioscience Engineering
15. Has specialized knowledge of complex biosystems and can apply this knowledge to design, implement and evaluate novel methodologies to solve technical problems in an environment where bioinformatics is used.
    
    Major Engineering and Bioscience Engineering
16. Has advanced skills in data analysis methodologies and can apply these skills to integrate data from multiple disciplines to solve bioinformatics problems in scientific, clinical or biotechnological environments.

Further Studies

Direct:

• Postgraduate Studies in Advanced Medical Imaging (Leuven)