Introduction to Ontologies, Pathways, and Networks

Matt Rogon   2016-10-04   Comments Off on Introduction to Ontologies, Pathways, and Networks

Date(s) - 2016-10-04 - 2016-10-06
09:00 CEST - 15:00 CEST


Introduction to Ontologies, Pathways, and Networks

Dates: 04 – 06 October 2016
Location: Seminar Room 202, Heidelberg
Requirements: laptops and enthusiasm
This course is free and open to all, including outstations.
During the workshop you will learn how to perform a range of basic computational tasks in analysis and
visualisation of biological data using online tools and Cytoscape.

You will learn how to:

  • Use public resources (databases such as String, pathway tools e.g. Reactome, and text mining) to explore their data
  • Construct biological networks, import and integrate experimental data
  • Apply basic concepts in visualisation to analyse, and interpret biological information.
  • Perform enrichment and depletion tests against ontologies and pathway databases

Schedule details:

Day 1

    1. Introduction to network biology

  • Introduction to Cytoscape
  • Loading and manipulating networks
  • Integrating experimental data

  • 2. Visualizing data on networks

  • Visual Styles – how to make pretty graphics
  • Automatic layouts can improve visualisations
  • Using data to enhance network graphics – displaying pie-charts, heatmaps,
    line charts etc. on networks
  • 3. Filtering complex networks using experimental measurements and metadata
    4. Protein/gene/transcript identifier systems such as Entrez, Ensembl, UniProt explained

Day 2
1. Using web services: String, IntAct, Complex Portal, Reactome, Kegg

2. Automating the retrieval of data from public resources

  • protein-protein interaction data (overview and usage of interaction databases)
  • integrative databases – introduction to STRING, IntAct
  • pathway databases – Reactome and KEGG
  • protein complexes – Complex Portal, Corum
  • how to do text mining
  • downloading entire interactomes
  • ——————————————————————————
    Day 3

      1. Enrichment analysis using ontologies (GO, KEGG, Reactome, Complexes, Drugs, Diseases)
      2. BYOD – bring your own data


    This event is fully booked.