Barlow T W
Physical Chemistry Laboratory, University of Oxford, U.K.
J Mol Graph. 1995 Feb;13(1):24-7, 53-5. doi: 10.1016/0263-7855(94)00007-f.
Self-organizing maps generated by Kohonen neural networks provide a method for transforming multidimensional problems into lower dimensional problems. Here, a Kohonen network is used to generate two-dimensional representations of the electrostatic potential about the ring structures of histamine H2 agonists. Previous work by J. Gasteiger and X. Li (Angew. Chem. Int. Ed. Engl. 1994, 33, 643) has shown the usefulness of such a method for classifying molecules as muscarinic or nicotinic agonists. Here, the method is extended to rank histamine H2 agonists in order of biological activity.
由科霍宁神经网络生成的自组织映射提供了一种将多维问题转化为低维问题的方法。在此，使用科霍宁网络生成组胺H2激动剂环结构周围静电势的二维表示。J. 加斯泰格和X. 李之前的工作（《德国应用化学》国际版，1994年，第33卷，643页）表明了这种方法在将分子分类为毒蕈碱或烟碱激动剂方面的有用性。在此，该方法被扩展用于按生物活性对组胺H2激动剂进行排序。
