6 ECTS credits
180 u studietijd
Aanbieding 1 met studiegidsnummer 4018221FNR voor alle studenten in het 2e semester met een gespecialiseerd master niveau.
This course focuses on algorithms and methods in computational biology, with active participation of the students in implementing such algorithms. The course covers methods and associated algorithms for solving problems related to i) protein sequences, protein evolution and protein structure, as well as ii) Next Generation Sequencing data analysis and strategies for the discovery of regulatory motifs, in particular genomics and transcriptomics data in relation to cancer.
The aims of the course are to i) familiarise students with the background and concepts in these two fields, ii) give students insight in how data, computational methodology and results are interconnected in Computational Biology and Bioinformatics, iii) enable the student to implement algorithms in these fields and iv) critically investigate the results produced by such algorithms. This knowledge should enable the students to understand the literature on bioinformatics and computational biology.
This is achieved through a) lectures to transfer the basic concepts, including article fragments to train the student in how to extract information from scientific literature, b) one project where the data and algorithm are provided, and where the focus is on the analysis of results (individual), and c) a final exam project where a relevant scientific article is reimplemented, critically assessed and presented (in student pairs).
More information is available via the 'Teaching' tab at http://we.vub.ac.be/en/wim-vranken.
Recognition of key terms in computational biology and bioinformatics, and awareness of algorithms to solve biological or medical questions. Implementation of an algorithm from computational biology or bioinformatics.
Ability to communicate constructively with peers in a joint project, and the clear and succinct presentation of information contained in a scientific article.
Understanding the concepts behind computational biology and bioinformatics, and application of this knowledge to algorithms that analyse or predict biological data. This includes awareness of pitfalls in using biological data, such as data quality, and bias or overlap in the data used.
Analysis of the outcomes of your algorithms, with critical assessment of whether they perform correctly (or not).
Evaluation of a presentation on a scientific article by your peers, including giving constructive and critical feedback about any concerns you might have.
Critical reading and active implementation of a scientific article in this field, with synthesis of the key points, to be communicated in a presentation.
De beoordeling bestaat uit volgende opdrachtcategorieën:
Examen Mondeling bepaalt 75% van het eindcijfer
ZELF Praktijkopdracht bepaalt 25% van het eindcijfer
Binnen de categorie Examen Mondeling dient men volgende opdrachten af te werken:
Binnen de categorie ZELF Praktijkopdracht dient men volgende opdrachten af te werken:
The evaluation is based on i) one project contributing 25% of the project points, with focus on the analysis of results from a bioinformatics approach (individual) and ii) a project where an existing published method from the field is re-implemented and presented (at the exam, in groups of two). Grades are assigned depending on the quality of the project in terms of the implementation and the analysis of the results, the presentation of the article and the critical insights by the student, and the participation during the exam. All source material has to be correctly referenced: plagiarism of code or text is not allowed and will result in a zero score.
Deze aanbieding maakt deel uit van de volgende studieplannen:
Bachelor in de wiskunde en Data Science: Standaard traject
Master in de ingenieurswetenschappen: toegepaste computerwetenschappen: Standaard traject
Master in de ingenieurswetenschappen: computerwetenschappen: afstudeerrichting Artificiële Intelligentie
Master in de ingenieurswetenschappen: computerwetenschappen: afstudeerrichting Multimedia
Master in de ingenieurswetenschappen: computerwetenschappen: afstudeerrichting Software Languages and Software Engineering
Master in de ingenieurswetenschappen: computerwetenschappen: afstudeerrichting Data Management en Analytics
Master in Applied Sciences and Engineering: Computer Science: Artificial Intelligence (enkel aangeboden in het Engels)
Master in Applied Sciences and Engineering: Computer Science: Multimedia (enkel aangeboden in het Engels)
Master in Applied Sciences and Engineering: Computer Science: Software Languages and Software Engineering (enkel aangeboden in het Engels)
Master in Applied Sciences and Engineering: Computer Science: Data Management and Analytics (enkel aangeboden in het Engels)