Affiliations
Institute for Bioinformatics and Systems Biology, Helmholtz Zentrum
München—German Research Center for Environmental Health,
Neuherberg, Germany,
Max Planck Institute for Dynamics and Self-Organization,
Göttingen, Germany
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Hypergraphs are also useful utilizing prior knowleges with multiple types of data integration
Posted by taehyun
on
29 Jul 2009 at 15:38 GMT
Thanks for an interesting perspective on hypergraphs. We published a hypergraph-based learning algorithm to integrate gene expression and protein-protein interaction data for cancer outcome prediction. And more comprehensive hypergraph-based learning algorithm paper recently accepted by Bioinformatic journal.
You can find the first conference paper: "Learning on Weighted Hypergraphs to Integrate Protein Interactions and Gene Expressions for Cancer Outcome Prediction"
