| Literature DB >> 22889967 |
Ichigaku Takigawa1, Hiroshi Mamitsuka.
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.Mesh:
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Year: 2012 PMID: 22889967 DOI: 10.1016/j.drudis.2012.07.016
Source DB: PubMed Journal: Drug Discov Today ISSN: 1359-6446 Impact factor: 7.851