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Dehmer M.,University of Federal Defense Munich | Dehmer M.,Division for Bioinformatics and Translational Research | Emmert-Streib F.,Queens University of Belfast | Shi Y.,Nankai University
PLoS ONE | Year: 2014

In this paper, we derive interrelations of graph distance measures by means of inequalities. For this investigation we are using graph distance measures based on topological indices that have not been studied in this context. Specifically, we are using the well-known Wiener index, Randić index, eigenvalue-based quantities and graph entropies. In addition to this analysis, we present results from numerical studies exploring various properties of the measures and aspects of their quality. Our results could find application in chemoinformatics and computational biology where the structural investigation of chemical components and gene networks is currently of great interest. © 2014 Dehmer et al. Source

Dehmer M.,Division for Bioinformatics and Translational Research | Emmert-Streib F.,Queens University of Belfast | Tripathi S.,Division for Bioinformatics and Translational Research
PLoS ONE | Year: 2013

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. © 2013 Dehmer et al. Source

Dander A.,Division for Bioinformatics and Translational Research | Dander A.,Innsbruck Medical University | Dander A.,Center for Personalized Medicine | Mueller L.A.J.,Division for Bioinformatics and Translational Research | And 7 more authors.
Source Code for Biology and Medicine | Year: 2013

Background: Molecular descriptors have been extensively used in the field of structure-oriented drug design and structural chemistry. They have been applied in QSPR and QSAR models to predict ADME-Tox properties, which specify essential features for drugs. Molecular descriptors capture chemical and structural information, but investigating their interpretation and meaning remains very challenging.Results: This paper introduces a large-scale database of molecular descriptors called COMMODE containing more than 25 million compounds originated from PubChem. About 2500 DRAGON-descriptors have been calculated for all compounds and integrated into this database, which is accessible through a web interface at http://commode.i-med.ac.at. © 2013 Dander et al.; licensee BioMed Central Ltd. Source

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