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Mining the enriched subgraphs for specific vertices in a biological graph

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Abstract
In this paper, we present a subgroup discovery method to find subgraphs in a graph that are associated with a given set of vertices. The association between a subgraph pattern and a set of vertices is defined by its significant enrichment based on a Bonferroni-corrected hypergeometric probability value. This interestingness measure requires a dedicated pruning procedure to limit the number of subgraph matches that must be calculated. The presented mining algorithm to find associated subgraph patterns in large graphs is therefore designed to efficiently traverse the search space. We demonstrate the operation of this method by applying it on three biological graph data sets and show that we can find associated subgraphs for a biologically relevant set of vertices and that the found subgraphs themselves are biologically interesting.
Keywords
Proteins, Data mining, Protein engineering, Diseases, Algorithm design and analysis, Life sciences, Subgraph mining, single graph, subgroup discovery, transcriptional regulatory network, protein graph, ALGORITHM, DATABASE, GENES, TOOL

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MLA
Meysman, Pieter, et al. “Mining the Enriched Subgraphs for Specific Vertices in a Biological Graph.” IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, vol. 16, no. 5, 2019, pp. 1496–507.
APA
Meysman, P., Saeys, Y., Sabaghian, E., Bittremieux, W., Van de Peer, Y., Goethals, B., & Laukens, K. (2019). Mining the enriched subgraphs for specific vertices in a biological graph. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 16(5), 1496–1507.
Chicago author-date
Meysman, Pieter, Yvan Saeys, Ehsan Sabaghian, Wout Bittremieux, Yves Van de Peer, Bart Goethals, and Kris Laukens. 2019. “Mining the Enriched Subgraphs for Specific Vertices in a Biological Graph.” IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 16 (5): 1496–1507.
Chicago author-date (all authors)
Meysman, Pieter, Yvan Saeys, Ehsan Sabaghian, Wout Bittremieux, Yves Van de Peer, Bart Goethals, and Kris Laukens. 2019. “Mining the Enriched Subgraphs for Specific Vertices in a Biological Graph.” IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 16 (5): 1496–1507.
Vancouver
1.
Meysman P, Saeys Y, Sabaghian E, Bittremieux W, Van de Peer Y, Goethals B, et al. Mining the enriched subgraphs for specific vertices in a biological graph. IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS. 2019;16(5):1496–507.
IEEE
[1]
P. Meysman et al., “Mining the enriched subgraphs for specific vertices in a biological graph,” IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, vol. 16, no. 5, pp. 1496–1507, 2019.
@article{8522581,
  abstract     = {In this paper, we present a subgroup discovery method to find subgraphs in a graph that are associated with a given set of vertices. The association between a subgraph pattern and a set of vertices is defined by its significant enrichment based on a Bonferroni-corrected hypergeometric probability value. This interestingness measure requires a dedicated pruning procedure to limit the number of subgraph matches that must be calculated. The presented mining algorithm to find associated subgraph patterns in large graphs is therefore designed to efficiently traverse the search space. We demonstrate the operation of this method by applying it on three biological graph data sets and show that we can find associated subgraphs for a biologically relevant set of vertices and that the found subgraphs themselves are biologically interesting.},
  author       = {Meysman, Pieter and Saeys, Yvan and Sabaghian, Ehsan and Bittremieux, Wout and Van de Peer, Yves and Goethals, Bart and Laukens, Kris},
  issn         = {1545-5963},
  journal      = {IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS},
  keywords     = {Proteins,Data mining,Protein engineering,Diseases,Algorithm design and analysis,Life sciences,Subgraph mining,single graph,subgroup discovery,transcriptional regulatory network,protein graph,ALGORITHM,DATABASE,GENES,TOOL},
  language     = {eng},
  number       = {5},
  pages        = {1496--1507},
  title        = {Mining the enriched subgraphs for specific vertices in a biological graph},
  url          = {http://dx.doi.org/10.1109/tcbb.2016.2576440},
  volume       = {16},
  year         = {2019},
}

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