Krause G, Streich W J, Franke R
Pharmazie. 1980 Aug;35(8):488-94.
Results from parallel tests with similar biological objects are frequently interrelated. If the data are discrete which is a typical situation in biological mass-screening, the information-theoretical concept of Shannon's entropy can be used to unreval redundancies within such test and to recognize tests with high informational content. This concept was applied to two examples from the screening for fungicidal activity, and the results were compared with activity-activity relationships obtained from pattern recognition and with variance analysis. There was good agreement, and the entropy calculation indeed yielded a very sensitive measure for the informational structure of the data. If the informational structure is known redundant tests may be eliminated. If the evaluation of quantitative structure-activity relationships is attempted it is furthermore possible to restrict the calculations to key tests with high information.
使用类似生物对象进行的平行测试结果常常相互关联。如果数据是离散的(这在生物大规模筛选中是典型情况),那么香农熵的信息论概念可用于揭示此类测试中的冗余,并识别具有高信息含量的测试。该概念应用于杀菌剂活性筛选的两个实例,并将结果与模式识别得到的活性-活性关系以及方差分析进行比较。结果吻合良好,熵计算确实为数据的信息结构提供了非常灵敏的度量。如果已知信息结构,就可以消除冗余测试。此外,如果尝试评估定量构效关系,还可以将计算限制在具有高信息的关键测试上。