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UZH BIO390 - Learning Goals

This page indicates some of the learning goals, as emphasised by the different lecturers. Some points will have been discussed in different lectures; accordingly, exam questions may not refer to information of one specific presentation.

Cave: Please be aware that some of the "Learning Goals" may reflect aspects not necessarily captured by the lectures in the current semester - The ones reelevant for the current semester's exam are related to the given lectures. Also, updates may occurr at any time.

Bioinformatics: Definition & Concepts

  • definition of "Bioinformatics" (cf. Anna Tramontano)
  • categories of informatics tools used in bioinformatics
  • hypothesis versus data driven science
  • areas of bioinformatics/bioinformaticians, (in contrast to "pure" modelling, statistics etc.)
  • 3 main categories of biological data, and example resources
  • definition of API
  • common sequence related file formats
  • hierarchies and relationships as 2 main principles of ontologies
  • areas of "not-bioinformatics", and why
  • bioinformatics tools (programming languages, libraries, online resources) and their specific use cases

Bioinformatics tools & resources

  • common programming/analysis languages in bioinformatics and their preferred use
  • components of bioinformatics online resources

Sequence Analysis

  • substitution matrices

Statistical Bioinformatics

  • usage of gene expression profiling
  • multiple testing correction
  • parameters for hierarchical clustering
  • statistical evidence for a change in the mean
  • dimensionality reduction
  • central limit theorem
  • hierarchical clustering
  • clustering coefficient

Regulatory Genomics and Epigenomics

  • secondary/tertiary human genome structure
  • functional genome content
  • transcription factors & genome interaction
  • chemical genome modifications, their effectors and results
  • Chip-Seq
  • read mapping
  • peak calling
  • sequence compression algorithms


  • concept of taxonomic diversity
  • concept microbial community dissimilarity
  • how are sequences used to derive an adopted species concept for prokaryotes
  • principle steps for 16S rRNA-based taxonomic composition analysis
  • essential steps of short sequencing read assembly into contigs and scaffolds
  • basic steps of metagenomic analysis: from raw reads to the reconstruction of genomic scaffolds


  • principles of proteome organization in the cell
  • key experimental and computational concepts for the collection and analysis of high confidence protein-protein interaction data
  • peptide fragmentation
  • target-decoy approach
  • protein quantification

Clinical Bioinformatics & Personalized Medicine

  • genomic variants (types, numbers)
  • genomic privacy and re-identification (concepts)
  • reference genome(s)
  • main bottlenecks of molecular diagnostics in the clinical setting
  • goals of many personalized health initiatives
  • direct-to-consumer genetic testing -> what, how
  • currently favoured clinical NGS technology
  • clinical trial participation
  • genotype-phenotype (G2P) (ab-)use

Text Mining

  • text mining pipelines & (current) common programs/applications
  • article/literature repositories (with focus on accessibility)
  • processing steps in text mining
  • common problems in text mining
  • search engine precision metrics
  • benchmarking

Semantic web, RDF, Ontologies

  • semantic web and its benefits
  • stack of standards in semantic web and their functions
  • RDF for modeling data
  • OWL/OBO for modeling a biomedical domain
  • querying knowledge graphs for answering biomedical questions

Biological Networks

  • Protein interaction and metabolic networks
  • the two-hybrid assay and its limitations
  • detection of protein complexes
  • graphs, nodes, edges, paths
  • geodesics, graph diameter
  • common types of degree distributions
  • adjacency matrix
  • shortest path matrix
  • assortative and disassortative graphs
  • community (module) detection
  • cliques
  • motifs, graph representations of metabolic networks

Genomic data & provacy

  • reasons for needing many genomes
  • principle of re-identification attacks over the Beacon protocol
  • long range familial searches
  • opinions about risk vs. opportunities
  • technical and regulatory solutions against privacy breaches & data abuse