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Automatic classification of chemical structure databases using a highly parallel array processor
Author(s) -
Rasmussen Edie M.,
Downs Geoffrey M.,
Willett Peter
Publication year - 1988
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.540090413
Subject(s) - computer science , cluster analysis , database , ibm , table (database) , data mining , parallel computing , artificial intelligence , materials science , nanotechnology
This article describes the use of the ICL Distributed Array Processor (DAP) for the automatic classification of chemical structure databases using the Jarvis‐Patrick clustering method. This method is based upon the calculation of a table containing the nearest neighbors for each of the molecules in the database which is to be clustered. These nearest neighbors can be identified very efficiently using the DAP since it allows up to 4096 molecules to be compared with a specified molecule in parallel. Experiments with files of 4096 and 8192 structures from the Fine Chemicals Database show that clustering with the DAP is up to 6.7 times as fast as using a highly efficient, inverted file algorithm on an IBM 3083 mainframe.