# Introduction to Computational Biology

Course Code : | 1000WETCOB |

Study domain: | Computer Science |

Academic year: | 2017-2018 |

Semester: | 2nd semester |

Sequentiality: | - |

Contact hours: | 0 |

Credits: | 3 |

Study load (hours): | 84 |

Contract restrictions: | No contract restriction |

Language of instruction: | Dutch |

Exam period: | exam in the 2nd semester |

Lecturer(s) | Kris Laukens |

### 1. Prerequisites *

- competences corresponding the final attainment level of secondary school

an active knowledge of

- Dutch

- English

Some lectures will either be presented in English, or make use of slides in English: the student is expected to have no difficulties in following these lectures. Some papers that may need to be read may also be in English.

- general knowledge of the use of a PC and the Internet

specific prerequisites for this course

This interdisciplinary course assumes that you have basic programming skills (language noit specified).

### 2. Learning outcomes *

- Having insights in the nature of the problems to which the field of computational biology can offer an answer.
- Understanding how a biological question can be formulated as a computational problem.
- Understanding how diverse computational techniques can be utilized to tackle problems from an other, for the student less-known science domain.
- Applying computational skills in an interdisciplinary context.

### 3. Course contents *

Computational biology consists of the use of techniques such as computational simulations, data analysis and mathematical modeling to study a large collection of biological problems.

In this course we will always start from a specific biological problem and discuss how computational techniques are used to obtain a solution.

For some of the topics we will involve external experts. Each of these topics starts with the definition of the biological problem, in a way that does not assume prior biological knowledge. Some examples of topics (possibly) covered:

- Study of metabolic fluxes.
- Modelling of growth
- Modelling of locomotion
- Climate models
- Biological evolution
- Computational neurobiology
- Social networks and population dynamics
- Molecular interaction networks
- Bio-inspired computing
- Ciomputing with biomolecules
- Genetics

There exist quite a few different definitions of computational biology, making the distinction with bioinformatics not always clear. In UAntwerpen curriculum we offer both courses, and we distinguish the fields as follows. Computational biology differs from bioinformatics in terms of both the biological and computational terms of scope. Bioinformatics is a more narrowly defined discipline which focuses on the use of data science and information theory techniques for interpreting biomolecular data such as DNA and RNA. Computational biology involves a much wider range of biological applications, and also makes use of mathematical modeling and computer simulations.

### 4 International dimension*

### 5. Teaching method and planned learning activities

Personal work

Project

Project

### 6. Assessment method and criteria

Written assignment

Presentation

### 7. Study material *

#### 7.1 Required reading

Study material will be offered by the lecturers.

**7.2 Optional reading**

The following study material can be studied voluntarily :-

### 8. Contact information *

Prof. dr. Kris Laukens

Advanced database research and modelling (ADReM) Lab.

Dept. Mathematics & Computer Science

University of Antwerp

Middelheimlaan 1, G.111

B-2020

Antwerpen, Belgium

T +32 (0)3 265 33 10

E kris.laukens@uantwerpen.be