Development of a spectral clustering method for the analysis of molecular data sets
Development of a spectral clustering method for the analysis of molecular data sets
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DOI：
10.1021/ci600565r
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发表时间：
2007-09-01
影响因子：
5.6
通讯作者：
Brewer, Mark L.
中科院分区：
文献类型：
--
作者：
Brewer, Mark L.
提出了一种光谱聚类方法并应用于二维分子结构，在该结构中发现它在筛选数据的分析中特别有用。该方法提供了一种量化集群内分子间相似性程度的方法，以及（2）分子的特征对群集的贡献。在将光谱聚类方法应用于125个COX-2抑制剂的示例数据集中，这两个标准被用来将分子放入化学相关的二维结构簇中。
A spectral clustering method is presented and applied to two-dimensional molecular structures, where it has been found particularly useful in the analysis of screening data. The method provides a means to quantify (1) the degree of intermolecular similarity within a cluster and (2) the contribution that the features of a molecule make to a cluster. In an application of the spectral clustering method to an example data set of 125 COX-2 inhibitors, these two criteria were used to place the molecules into clusters of chemically related two-dimensional structures.