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Statistical Methods for the Analysis of Gene Expression Data
Statistische Methoden für die Analyse von Genexpression
Last Updated: 2026-02-05 15:24:49
Abstract
The lecture discusses the complete analysis of gene expression data and covers the dedicated methods of data preprocessing, data exploration, inference, classification, and functional analysis. The lecture treats especially the application of statistical methods in the situation where many variables are measured for few subjects.
Content
The lecture discusses the complete analysis of gene expression data and covers the dedicated methods of data preprocessing, data exploration (clustering, principal component analysis, ...), inference (hypothesis testing, ...), classification (nearest neighbor, support vector machines, ...) and functional analysis (pathway and network analyses). The lecture treats especially the application of statistical methods in the situation where many variables (ca. 10000 genes) are measured for few subjects (ca. 3-10, patients, plants, cell cultures, ...). Further we give consideration to the non-negligible systematic and random errors that occur in the measurement of gene expression. Measuring the gene expression or gene "activity" is currently one of the most important tools for the understanding of molecular processes in cells. On the one hand, the gene expression determines the identity of the proteins produced und thus the molecular functions a cell user, and on the other hand measuring the expression for all genes simultaneously is rather easy (as compared to measuring the expression of all proteins simultaneously). Measurement is done typically by microarrays, and more recently also by massively parallel sequencing with the latest sequencing machines.
General Information
- Language
- German
- Levels
- MSC
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Statistische Methoden für die Analyse von Genexpression
**Kurs an der Uni Zürich**
Lehrveranstaltungsnummern: 3029, 3030
|
|
1.5 h weekly |