[Networkit] Disease Module Identification Challenge
aleksejs.sazonovs at gmail.com
Fri Jul 15 18:12:57 CEST 2016
DREAM Challenges are quite a big thing in the systems biology community. If
NK does well, it would probably get some good publicity among that crowd.
I haven't read the full set of rules, but it seems that they are actively
prohibiting the use of any prior biological knowledge (gene ontologies,
interaction databases, etc). Hence, the challenge is almost purely about
I'm very interested in trying to use NK for this task. Email me (
as2537 at cam.ac.uk), if somebody wants to work on this together.
On Fri, Jul 15, 2016 at 4:45 PM, Christian Staudt <christian.staudt at kit.edu>
> "We have compiled a unique collection of a dozen as yet unpublished
> genomic networks for human, which were contributed by eight different
> groups for this challenge. This collection includes state-of-the-art
> protein-protein interaction networks, signaling networks, regulatory
> networks and co-expression networks, among others.
> Participants are challenged to apply network module identification methods
> (also known as community detection or graph clustering methods) to predict
> functional modules based on network topology. ”
> This challenge provides a much needed real-world problem setting for
> community detection algorithms. The “prize” is coauthorship to their paper.
> Perhaps someone reading this feels motivated to take part using NetworKit’s
> Thanks Aleksejs Sazonovs for the link.
> NetworKit mailing list
> NetworKit at ira.uni-karlsruhe.de
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