Network biology

Netter: re-ranking gene network inference predictions using structural network properties

Background: Many algorithms have been developed to infer the topology of gene regulatory networks from gene expression data. These methods typically produce a ranking of links between genes with associated confidence scores, after which a certain threshold is chosen to produce the inferred topology. However, the structural properties of the predicted network do not resemble those typical for a gene regulatory network, as most algorithms only take into account connections found in the data and do not include known graph properties in their inference process.

May
23
May/23 09:00 - May/27 18:00
Delft University of Technology (TUD), Delft, the Netherlands

BioSB Course: Algorithms for Biological Networks (4rd edition)

• Date: 23-27 May 2016
• Course coordinators: Dick de Ridder (WUR), Jeroen de Ridder (TUD)
• Website: http://biosb.nl/education/course-portfolio/course-algorithms-for-biologi...

Target audience

PhD students with a background in bioinformatics, computer science or a related field; a working knowledge of basic statistics and linear algebra is assumed.

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