Bioinformatics
Learning outcomes
After the course, the student can:
- compare sequencing and microarray technologies used in high-throughput
analysis and choose suitable ones for the analysis required.
- explain the principles of measurement technologies covered and how
various inherent errors and biases of the measurement techniques affect
the analysis.
- apply common methods and algorithms to extract information from
microarray and sequencing measurements.
- discuss the statistical principles underlying the data analysis
methods above and identify the benefits and weaknesses of each method.
- select suitable algorithms for the analysis and justify the choice.
- build data analysis pipelines for microarray and sequencing data
analysis.
Contents
Deep sequencing technologies
DNA microarrays
Statistical methods for the analysis of high-throughput measurement data
Data classification and clustering
Modes of study
- Degree Programme Students
- Other Students
- Open University Students
- Doctoral Students
- Exchange Students
Lectures 20 h
Independent work 14 h
Independent work by following the provided instructions
