RESQUE: Network Reduction Using Semi-Markov Random Walk Scores for Efficient Querying of Biological Networks (Extended Abstract)
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In this work, we present RESQUE, an efficient algorithm for querying large-scale biological networks. The algorithm uses a semi-Markov random walk model to estimate the correspondence scores between nodes across different networks. The target network is iteratively reduced based on the node correspondence scores, which are also iteratively re-estimated for improved accuracy, until the best matching subnetwork emerges. The proposed network querying scheme is computationally efficient, can handle any network query with arbitrary topology, and yields accurate querying results. © 2012 Springer-Verlag Berlin Heidelberg.
author list (cited authors)
Sahraeian, S., & Yoon, B.