Introduction presentation

You can download the presentation from here.


As a start of the hands-on session, we prepared a short quiz. You can work alone or in a group (up to 4 people).
After the quiz there will be a coffee break before we start with the tutorial at 11:00.

We have a Winner !

Team “iSLD”


Prize arriving soon…. Don’t forget to collect it 🙂


In this tutorial you are going to perform pathway analysis in PathVisio to help biological interpretation. You are going to:

  • Search for regulated pathways that might be relevant to study in more detail.
  • Visualize your data on a pathway diagram so you can explore the data in a biological context.

First read the small text about WikiPathways below (you don’t need to click on the links, unless you want more background info) and then continue with the PathVisio-based analysis of a dataset from the diXa data warehouse by going to: Pathway Analysis

Background Information


WikiPathways was established to facilitate the contribution and maintenance of pathway information by the biology community. WikiPathways is an open, collaborative platform dedicated to the curation of biological pathways. WikiPathways thus presents a new model for pathway databases that enhances and complements ongoing efforts, such as KEGG, Reactome and Pathway Commons. Building on the same MediaWiki software that powers Wikipedia, we added a custom graphical pathway editing tool and integrated databases covering major gene, protein, and small-molecule systems. The familiar web-based format of WikiPathways greatly reduces the barrier to participate in pathway curation. More importantly, the open, public approach of WikiPathways allows for broader participation by the entire community, ranging from students to senior experts in each field. This approach also shifts the bulk of peer review, editorial curation, and maintenance to the community.


PathVisio is a tool for displaying and editing biological pathways. In a sense PathVisio lets you draw pathways as you would in any drawing program, like PowerPoint or Photoshop. But the difference is that PathVisio can understand the biological context of a pathway, because you can link biological entities (genes or proteins) in your pathways to biological data using database identifiers. This will let you map experimental data (e.g. microarray data) and visualize it on top of the pathway drawing. PathVisio 3 allows you do to load your dataset, visualize the data on the pathways and perform pathway statistics. The new plugin manager facilitates the installation of additional plugins to perform more advanced pathway analysis.