SCODE

This is the Cytoscape app implementation for Protein Complex Identification by Supervised Graph Clustering
This app implements an algorithm (originally described by [http://www.cs.cmu.edu/~qyj/SuperComplex Qi et al]) for protein complex identification in PPI networks based on features specified in a Bayesian network structure. Using supervised learning, a Bayesian template may be trained with a list of known complexes and used to score candidates using real-valued data provided in the PPI graph. Candidate complexes are expanded according to one of three possible variants of iterative simulated annealing: Simple ISA, Greedy ISA, and Sorted-Neighbor ISA. For details on each of these search algorithms, see the [https://github.com/DataFusion4NetBio/Paper16-SCODE/blob/master/Demo/SCODEUserManual.pdf User Manual]. Resulting complexes may be evaluated to determine the app's performance using a user-provided set of testing complexes. For more resources and sample files, check out the [https://github.com/DataFusion4NetBio/Paper16-SCODE/tree/master/Demo GitHub Demo folder].

1.0.4

Works with Cytoscape 3.2


1.0.3

Works with Cytoscape 3.2


1.0.2

Works with Cytoscape 3.2


1.0.1

Works with Cytoscape 3.2


1.0.0

Works with Cytoscape 3.2


CYTOSCAPE 3

Version 1.0.4

License Click here

Released 1 Jul 2016

Works with Cytoscape 3.2

Download Stats Click here