[Networkit] Disease Module Identification Challenge

Christian Staudt christian.staudt at kit.edu
Fri Jul 15 17:45:04 CEST 2016


"We have compiled a unique collection of a dozen as yet unpublished genomic networks for human, which were contributed by eight different groups for this challenge.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 components.

Thanks Aleksejs Sazonovs for the link.

-------------- next part --------------
A non-text attachment was scrubbed...
Name: signature.asc
Type: application/pgp-signature
Size: 495 bytes
Desc: Message signed with OpenPGP using GPGMail
URL: <http://lists.ira.uni-karlsruhe.de/pipermail/networkit/attachments/20160715/9b25ef35/attachment.sig>

More information about the NetworKit mailing list