Graph mining: procedure, application to drug discovery and recent advances.
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.
Bioinformatics Center, Institute for Chemical Research Kyoto University, Gokasho, Uji 6110011, Japan. takigawa@cris.hokudai.ac.jp
Ichigaku
I
Takigawa
Hiroshi
H
Mamitsuka
D020650:Combinatorial Chemistry Techniques / Q000379:methods*; D003196:Computer Graphics; D057225:Data Mining; D062126:Databases, Chemical; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods; D006801:Humans; D054852:Small Molecule Libraries
D054852:Small Molecule Libraries