MoSS: A Program for Molecular Substructure Mining
Borgelt C, Meinl T, Berthold MR (2005)
Publication Language: English
Publication Type: Conference contribution, Original article
Publication year: 2005
Publisher: IEEE
Edited Volumes: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Pages Range: 6-15
Conference Proceedings Title: Proceedings of Open Source Data Mining Workshop on Frequent Pattern Mining Implementations (OSDM 2005)
Event location: Chicago, IL
ISBN: 1-59593-210-0
URI: http://www2.informatik.uni-erlangen.de/publication/download/moss_osdm.pdf
Abstract
Molecular substructure mining is currently an intensively studied research area. In this paper we present an implementation of an algorithm for finding frequent substructures in a set of molecules, which may also be used to find substructures that discriminate well between a focus and a complement group. In addition to the basic algorithm, we discuss advanced pruning techniques, demonstrating their effectiveness with experiments on two publicly available molecular data sets, and briefly mention some other extensions. Copyright 2005 ACM.
How to cite
APA:
Borgelt, C., Meinl, T., & Berthold, M.R. (2005). MoSS: A Program for Molecular Substructure Mining. In Goethals, Bart ; Nijssen, Siegfried ; Zaki, Mohammed J. (Eds.), Proceedings of Open Source Data Mining Workshop on Frequent Pattern Mining Implementations (OSDM 2005) (pp. 6-15). Chicago, IL, US: IEEE.
MLA:
Borgelt, Christian, Thorsten Meinl, and Michael R. Berthold. "MoSS: A Program for Molecular Substructure Mining." Proceedings of the Open Source Data Mining Workshop on Frequent Pattern Mining Implementations (OSDM 2005), Chicago, IL Ed. Goethals, Bart ; Nijssen, Siegfried ; Zaki, Mohammed J., IEEE, 2005. 6-15.
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