Large-Scale Evaluation of Molecular Descriptors by Means of Clustering

Molecular descriptors have been explored extensively. From these studies, it is known that a large number of descriptors are strongly correlated and capture similar characteristics of molecules. In this paper, we evaluate 919 Dragon-descriptors of 6 different categories by means of clustering. Also,...

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Detalles Bibliográficos
Autores principales: Dehmer, Matthias, Emmert-Streib, Frank, Tripathi, Shailesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3877108/
https://www.ncbi.nlm.nih.gov/pubmed/24391854
http://dx.doi.org/10.1371/journal.pone.0083956
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author Dehmer, Matthias
Emmert-Streib, Frank
Tripathi, Shailesh
author_facet Dehmer, Matthias
Emmert-Streib, Frank
Tripathi, Shailesh
author_sort Dehmer, Matthias
collection PubMed
description Molecular descriptors have been explored extensively. From these studies, it is known that a large number of descriptors are strongly correlated and capture similar characteristics of molecules. In this paper, we evaluate 919 Dragon-descriptors of 6 different categories by means of clustering. Also, we analyze these different categories of descriptors also find a subset of descriptors which are least correlated among each other and, hence, characterize molecular graphs distinctively.
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spelling pubmed-38771082014-01-03 Large-Scale Evaluation of Molecular Descriptors by Means of Clustering Dehmer, Matthias Emmert-Streib, Frank Tripathi, Shailesh PLoS One Research Article Molecular descriptors have been explored extensively. From these studies, it is known that a large number of descriptors are strongly correlated and capture similar characteristics of molecules. In this paper, we evaluate 919 Dragon-descriptors of 6 different categories by means of clustering. Also, we analyze these different categories of descriptors also find a subset of descriptors which are least correlated among each other and, hence, characterize molecular graphs distinctively. Public Library of Science 2013-12-31 /pmc/articles/PMC3877108/ /pubmed/24391854 http://dx.doi.org/10.1371/journal.pone.0083956 Text en © 2013 Dehmer et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Dehmer, Matthias
Emmert-Streib, Frank
Tripathi, Shailesh
Large-Scale Evaluation of Molecular Descriptors by Means of Clustering
title Large-Scale Evaluation of Molecular Descriptors by Means of Clustering
title_full Large-Scale Evaluation of Molecular Descriptors by Means of Clustering
title_fullStr Large-Scale Evaluation of Molecular Descriptors by Means of Clustering
title_full_unstemmed Large-Scale Evaluation of Molecular Descriptors by Means of Clustering
title_short Large-Scale Evaluation of Molecular Descriptors by Means of Clustering
title_sort large-scale evaluation of molecular descriptors by means of clustering
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3877108/
https://www.ncbi.nlm.nih.gov/pubmed/24391854
http://dx.doi.org/10.1371/journal.pone.0083956
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