ISSN:
1572-8897
Source:
Springer Online Journal Archives 1860-2000
Topics:
Chemistry and Pharmacology
,
Mathematics
Notes:
Abstract A non-linear neural network model to perform cluster analysis is presented. It provides an efficient parallel algorithm for solving this pattern recognition task, consisting, from the mathematical point of view, of a combinatorial optimization problem. A new classification technique is discussed in order to visualize clustering patterns within a molecular set, by means of numerical analysis of the similarity matrix. As an example of the application of the reported neural network model, a quantum molecular similarity study in the field of structure-activity relationships is reported. A molecular set made of eighteen quinolones is used as an example. The resultant cluster distribution showed a good qualitative correlation between similarity data and biological activity.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01165355
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