[ 675INTR13 ] Subject Introduction to R

Workload Mode of examination Education level Study areas Responsible person Coordinating university
3 ECTS Structure B2 - Bachelor's programme 2. year (*)Bioinformatik Ulrich Bodenhofer Johannes Kepler University Linz
Detailed information
Original study plan Bachelor's programme Bioinformatics 2015W
Objectives This course is meant to show how to approach and solve problems in bioinformatics and computational biology with tools supplied by R. The focus is on data analysis with machine learning methods and visualizing the results of this analysis.
Subject The scientific computing platform (and programming language) R was originally designed for statistical analyses, but it has quickly emerged as a de facto standard in bioinformatics. It is also rapidly gaining importance in machine learning. So R is definitely a platform of the future. To know R well is a great plus in statistics and machine learning, and it is even a must in bioinformatics.

The course is divided into two parts:

1. The R platform and programming language

  • Introduction
  • The R programming language
  • R graphics
  • Sweave
  • Object-oriented programming in R
  • Foreign language interfaces
  • Packaging

2. Applications in bioinformatics

  • Bioconductor
  • Sequence handling and alignment
  • Phylogeny
  • Analyzing gene expression data
  • Genome analysis
Subordinated subjects, modules and lectures