文章基本信息

标题：Application of Information—Theoretic Concepts in Chemoinformatics
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作者：Martin Vogt ; Anne Mai Wassermann ; Jürgen Bajorath 等
期刊名称：Information
电子版ISSN：2078-2489
出版年度：2010
卷号：1
期号：2
页码：60-73
DOI：10.3390/info1020060
语种：English
出版社：MDPI Publishing
摘要：The use of computational methodologies for chemical database mining and molecular similarity searching or structure-activity relationship analysis has become an integral part of modern chemical and pharmaceutical research. These types of computational studies fall into the chemoinformatics spectrum and usually have large-scale character. Concepts from information theory such as Shannon entropy and Kullback-Leibler divergence have also been adopted for chemoinformatics applications. In this review, we introduce these concepts, describe their adaptations, and discuss exemplary applications of information theory to a variety of relevant problems. These include, among others, chemical feature (or descriptor) selection, database profiling, and compound recall rate predictions.
关键词：database profiling; feature selection; feature significance; information theory; similarity searching; molecular topology; virtual screening