Keywords
Learning outcomes
Mastering basics of probability theory (probability, probability axioms, conditional probability, probability density function, cumulative distribution function, expectation, variance, discrete random variable, continuous random variable). Ability to calculate with complex numbers and matrices (also determinant, eigenvalues and eigenvectors), and define extremum values of a given function. Capability to analyze and solve elementary differential equations.
Contents
Essential mathematics methods with applications to bioinformatics. The course content includes probability theory, complex numbers, matrices, ordinary differential equations, extremum values.
Teaching methods
| Teaching method | Contact | Online |
| Lectures | 14 h | 0 h |
| Exercises | 10 h | 0 h |
Teaching language
EnglishModes of study
- Degree Programme Students
- Other Students
- Open University Students
- Doctoral Students
- Exchange Students
Lectures, exercises, participation in classroom work (50% of home exercises must be completed) and Moodle activity (at lest 4 participations at the course discussion forum in Moodle), written exam.
Evaluation
Numeric 1-5.Study materials
Lecture notes and supplementary books.
Further information
In the academic year 2014-2015 the course BIO2310 Mathematics and Statistics for Bioinformatics 6 ECTS will replace the courses BIO2290 Mathematics for Bioinformatics 3 ECTS and BIO2270 Introduction to Statistics 3 ECTS.
Belongs to following study modules
2015–2016