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Drug Discov Today. 2013 Jan;18(1-2):50-7. doi: 10.1016/j.drudis.2012.07.016. Epub 2012 Aug 5.

Graph mining: procedure, application to drug discovery and recent advances.

Author information

1
Bioinformatics Center, Institute for Chemical Research Kyoto University, Gokasho, Uji 6110011, Japan. takigawa@cris.hokudai.ac.jp

Abstract

Combinatorial chemistry has generated chemical libraries and databases with a huge number of chemical compounds, which include prospective drugs. Chemical structures of compounds can be molecular graphs, to which a variety of graph-based techniques in computer science, specifically graph mining, can be applied. The most basic way for analyzing molecular graphs is using structural fragments, so-called subgraphs in graph theory. The mainstream technique in graph mining is frequent subgraph mining, by which we can retrieve essential subgraphs in given molecular graphs. In this article we explain the idea and procedure of mining frequent subgraphs from given molecular graphs, raising some real applications, and we describe the recent advances of graph mining.

PMID:
22889967
DOI:
10.1016/j.drudis.2012.07.016
[Indexed for MEDLINE]

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