RESQUE: Network Reduction Using Semi-Markov Random Walk Scores for Efficient Querying of Biological Networks (Extended Abstract) Conference Paper uri icon


  • 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.

published proceedings

  • Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

author list (cited authors)

  • Sahraeian, S., & Yoon, B.

citation count

  • 0

complete list of authors

  • Sahraeian, Sayed Mohammad Ebrahim||Yoon, Byung-Jun

publication date

  • May 2012