Algorithms for Regular Tree Grammar Network Search and Their Application to Mining Human-viral Infection Patterns

Ilan Smoly, Amir Carmel, Yonat Shemer-Avni, Esti Yeger-Lotem, Michal Ziv-Ukelson

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Network querying is a powerful approach to mine molecular interaction networks. Most state-of-the-art network querying tools either confine the search to a prespecified topology in the form of some template subnetwork, or do not specify any topological constraints at all. Another approach is grammar-based queries, which are more flexible and expressive as they allow for expressing the topology of the sought pattern according to some grammar-based logic. Previous grammar-based network querying tools were confined to the identification of paths. In this article, we extend the patterns identified by grammar-based query approaches from paths to trees. For this, we adopt a higher order query descriptor in the form of a regular tree grammar (RTG). We introduce a novel problem and propose an algorithm to search a given graph for the k highest scoring subgraphs matching a tree accepted by an RTG. Our algorithm is based on the combination of dynamic programming with color coding, and includes an extension of previous k-best parsing optimization approaches to avoid isomorphic trees in the output. We implement the new algorithm and exemplify its application to mining viral infection patterns within molecular interaction networks. Our code is available online.

Original languageEnglish
Pages (from-to)165-179
Number of pages15
JournalJournal of Computational Biology
Issue number3
StatePublished - 1 Mar 2016


  • RNA secondary structure
  • algorithms
  • computational molecular biology
  • phylogenetic trees
  • sequence analysis

ASJC Scopus subject areas

  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computational Mathematics
  • Computational Theory and Mathematics


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