Structural Discrimination of Networks by Using Distance, Degree and Eigenvalue-Based Measures
Open Access
- 6 July 2012
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 7 (7), e38564
- https://doi.org/10.1371/journal.pone.0038564
Abstract
In chemistry and computational biology, structural graph descriptors have been proven essential for characterizing the structure of chemical and biological networks. It has also been demonstrated that they are useful to derive empirical models for structure-oriented drug design. However, from a more general (complex network-oriented) point of view, investigating mathematical properties of structural descriptors, such as their uniqueness and structural interpretation, is also important for an in-depth understanding of the underlying methods. In this paper, we emphasize the evaluation of the uniqueness of distance, degree and eigenvalue-based measures. Among these are measures that have been recently investigated extensively. We report numerical results using chemical and exhaustively generated graphs and also investigate correlations between the measures.This publication has 30 references indexed in Scilit:
- Information Indices with High Discriminative Power for GraphsPLOS ONE, 2012
- A network-based approach to classify the three domains of lifeBiology Direct, 2011
- A history of graph entropy measuresInformation Sciences, 2011
- Network analysis using a novel highly discriminating topological indexComplexity, 2010
- New Polynomial-Based Molecular Descriptors with Low DegeneracyPLOS ONE, 2010
- Characterization of complex networks: A survey of measurementsAdvances in Physics, 2007
- On Highly Discriminating Molecular Topological IndexJournal of Chemical Information and Computer Sciences, 1996
- The Discrimination Ability of Some Topological and Information Distance Indices for Graphs of Unbranched Hexagonal SystemsJournal of Chemical Information and Computer Sciences, 1996
- Discrimination of isomeric structures using information theoretic topological indicesJournal of Computational Chemistry, 1984
- Isomer discrimination by topological information approachJournal of Computational Chemistry, 1981