Advances in Molecular Similarity

Advances in Molecular Similarity

First published on January 1, 1999

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  • Authors: R. Carbó-Dorca, P.G. Mezey
  • eBook ISBN: 9780080552262

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This volume highlights some of the advances in molecular similarity. Molecular similarity research is a dynamic field where the rapid transfer of ideas and methodologies from the theoretical, quantum chemical and mathematical chemistry disciplines to efficient algorithms and computer programs used in industrially important applications is especially evident. These applications often serve as motivating factors toward new advances in the fundamental and theoretical fields, and the combination of intellectual challenge and practical utility provides mutual advantages to theoreticians and experimentalists. The aim of this volume is to present an overview of the current methodologies of molecular similarity studies, and to point out new challenges, unsolved problems, and areas where important new advances can be expected.


For scientists and researchers interested or involved in the field of molecular similarities.

Table of Contents

  • Editorial forward (R. Carbó-Doca, P.G. Mezey). Quantum similarity (R. Carbó-Dorca et al.). Fuzzy sets and boolean tagged sets; vector semispaces and convex sets; quantum similarity measures and ASA density functions; diagonal vector spaces and quantum chemistry (R. Carbó-Dorca). Pattern recognition techniques in molecular similarity (W.G. Richards, D. Robinson). Topology and the quantum chemical shape concept (P.G. Mezey). Structural similarity analysis based on topological fragment spectra (Y. Takahashi et al.). Analysis of the transferability of similarity calculations from substructures to complex compounds (G. Sello, M. Termini). Similarity in organic synthesis design: comparing the syntheses of different compounds (G. Sello). Browsable structure-activity datasets (M. Johnson). Characterization of the molecular similarity of chemicals using topological invariants (S.C. Basak et al.). Optimizing hybrid density functionals by means of quantum molecular similarity techniques (M. Solá et al.). Atomic similarity through a neural network: self-associative periodic table of elements (J. Fayos). Comparison of quantum similarity measures derived from one-electron, intracule and extracule densities (X. Fradera et al.). The complementarity principle and its uses in molecular similarity and related aspects (J.R. Dias). Correlations and applications of the circumscribing/excised internal structure concept (J.R. Dias). Least-squares and neural-network forecasting from critical data: diatomic molecular re and triatomic IP and DHa (J. Wholers et al.). Index.

Product details

  • No. of pages: 296
  • Language: English
  • Copyright: © JAI Press 1999
  • Published: January 1, 1999
  • Imprint: JAI Press
  • eBook ISBN: 9780080552262

About the Authors

R. Carbó-Dorca

Affiliations and Expertise

Institute of Computational Chemistry, University of Girona, Girona, Spain

P.G. Mezey

Affiliations and Expertise

Departments of Chemistry and Mathematics and Statistics, University of Saskatchewan, Saskatoon, Canada

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