RESQUE: Network reduction using semi-Markov random walk scores for efficient querying of biological networks by Sayed Mohammad Ebrahim Sahraeian and Byung-Jun Yoon. (Bioinformatics (2012) 28 (16): 2129-2136. doi: 10.1093/bioinformatics/bts341)
Abstract:
Motivation: Recent technological advances in measuring molecular interactions have resulted in an increasing number of large-scale biological networks. Translation of these enormous network data into meaningful biological insights requires efficient computational techniques that can unearth the biological information that is encoded in the networks. One such example is network querying, which aims to identify similar subnetwork regions in a large target network that are similar to a given query network. Network querying tools can be used to identify novel biological pathways that are homologous to known pathways, thereby enabling knowledge transfer across different organisms.
Results: In this article, we introduce an efficient algorithm for querying large-scale biological networks, called RESQUE. The proposed algorithm adopts a semi-Markov random walk (SMRW) model to probabilistically estimate the correspondence scores between nodes that belong to different networks. The target network is iteratively reduced based on the estimated correspondence scores, which are also iteratively re-estimated to improve accuracy until the best matching subnetwork emerges. We demonstrate that the proposed network querying scheme is computationally efficient, can handle any network query with an arbitrary topology and yields accurate querying results.
Availability: The source code of RESQUE is freely available at http://www.ece.tamu.edu/~bjyoon/RESQUE/
If you promise not to tell, you can get a preprint version of the article at the source code link.
RESQUE: REduction-based scheme using Semi-Markov scores for networkQUEing.
Sounds like a starting point if you are interested in the Visualize This! (NSA Network Visualization Contest).
If you know of anyone looking for a tele-commuting researcher who finds interesting things, pass my name along. Thanks!