Entry requirements

A Bachelor's degree, equivalent to a Swedish Kandidatexamen, from an internationally recognised university. Also required is 45 credits in biology with 30 credits in molecular biology, cell biology, evolution and/or genetics; and 15 credits in mathematics/statistics.

Learning outcomes

To pass, the student should be able to:

• describe the key concepts covered in scientific computing and statistics, and perform tasks that require knowledge of these concepts;
• describe and apply algorithms and methods covered in the course;
• analyse properties of the computational algorithms, mathematical and statistical models, by using the analytical tools presented in the course;
• apply basic experimental design methods;
• solve computational problems in a structured way (by breaking down the problem into sub-problems) and implement in Matlab;
• write programs in C for solving scientific problems in the areas of biology and computational science.

Content

The course has three parts: scientific computing and basig programming, statistics and multivariate data analysis, programming in C.

Part 1(3 credits): Matrices, vectors and solution to linear equation systems through LU-factorisation. numerical solution to intgerals, introduction to Monte Carlo methods. Matlab and fundamentals in programming, e.g. control stuctures (if, for, while) and functions.

Part 2 (4 credits): Statistics and multivariate data analysis: fundamentals i statistics (distributions, expected value, varians, standard deviation etc.). Principal component analysis. Predictive multivariate data analysis.

Part 3 (3 credits): Programming: programming, testing and debugging in C. Data types, regular experssions, functions and modules. The content is to a high extent application driven, where problems in biology are used in assignments.

Instruction

Lectures, problem solving classes, computer lab, assignments.

Assessment

Written exam (part 1 and 2). Assignments (part 1, part 2 and part 3).