Information 2010, 1(2), 60-73; doi:10.3390/info1020060

Application of Information—Theoretic Concepts in Chemoinformatics

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Received: 1 September 2010; in revised form: 26 September 2010 / Accepted: 16 October 2010 / Published: 20 October 2010
(This article belongs to the Special Issue What Is Information?)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: 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.
Keywords: database profiling; feature selection; feature significance; information theory; similarity searching; molecular topology; virtual screening
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MDPI and ACS Style

Vogt, M.; Wassermann, A.M.; Bajorath, J. Application of Information—Theoretic Concepts in Chemoinformatics. Information 2010, 1, 60-73.

AMA Style

Vogt M, Wassermann AM, Bajorath J. Application of Information—Theoretic Concepts in Chemoinformatics. Information. 2010; 1(2):60-73.

Chicago/Turabian Style

Vogt, Martin; Wassermann, Anne Mai; Bajorath, Jürgen. 2010. "Application of Information—Theoretic Concepts in Chemoinformatics." Information 1, no. 2: 60-73.

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