[ 993TALSGATK19 ] KV (*)Genome Analysis & Transcriptomics

Es ist eine neuere Version 2023W dieser LV im Curriculum Masterstudium Artificial Intelligence 2023W vorhanden.
(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload Ausbildungslevel Studienfachbereich VerantwortlicheR Semesterstunden Anbietende Uni
3 ECTS B2 - Bachelor 2. Jahr Artificial Intelligence Sepp Hochreiter 2 SSt Johannes Kepler Universität Linz
Quellcurriculum Masterstudium Artificial Intelligence 2019W
Ziele (*)Bioinformatics is an interdisciplinary field at the interface of life sciences and computational sciences that deals with the development and application of methods for storing, retrieving, and, in particular, analyzing biological data. The massive data amounts produced by recent and currently emerging high-throughput biotechnologies provide unprecedented potentials, but also pose yet unseen computational challenges – making bioinformatics an essential success factor for the advancement of fields, such as, molecular biology, genetics, medicine, and pharmacology.

The goal of this course is to provide an overview of foundational and computational aspects of genetic variation and gene expression. The first part is mainly concerned with genetic commonalities and differences between individuals, how these commonalities and differences emerge, and how they can be associated to diseases and other traits. The second part is concerned with the dynamics of genes, how they are organized, how they can be detected, how the activation of genes is controlled, and how gene expression can be measured and analyzed computationally.

Lehrinhalte (*)Genome Analysis:

  • Single nucleotide variants/polymorphisms
  • Copy number variations and aberrations
  • Genotype-phenotype association studies
  • Linkage disequilibrium
  • Haplotype blocks
  • Identity by descent
  • Phasing and genotype imputation
  • Population genetics models


  • Gene expression
  • Microarrays
  • Next generation sequencing, read mapping, RNA-seq
  • Gene and promoter detection
  • Detection of splice sites and alternative splice sites
  • Epigenomics
  • Pathways and gene modules
Beurteilungskriterien (*)The final grade is based on a combined assessment of homework and a final exam.
Lehrmethoden (*)Slide presentations
Abhaltungssprache Englisch
Literatur (*)Electronic course material is made available for download
Lehrinhalte wechselnd? Nein
Sonstige Informationen (*)Until term 2019S known as: 675GTSBGATK13 Genome Analysis & Transcriptomics
Frühere Varianten Decken ebenfalls die Anforderungen des Curriculums ab (von - bis)
675GTSBGATK13: KV Genome Analysis & Transcriptomics (2013W-2019S)
Teilungsziffer 35
Zuteilungsverfahren Direktzuteilung