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Journal ArticleDOI

Some new trends in chemical graph theory.

TLDR
Unidad de Investigación de Diseño de Farmacos y Conectividad Molecular, Departamento de Quisica Fisica, Facultad of Farmacı́a, Universitat de València, Spain, Instituto de Tecnologia Quimica, CSIC-Universidad Politecnica de Valencia,
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Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review

TL;DR: It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates and an optimized protocol of network-aided drug development is suggested, and a list of systems-level hallmarks of drug quality is provided.
Journal ArticleDOI

Machine learning in chemoinformatics and drug discovery.

TL;DR: Basic principles and recent case studies are presented to demonstrate the utility of machine learning techniques in chemoinformatics analyses; and limitations and future directions are discussed to guide further development in this evolving field.
Journal ArticleDOI

Topological index based on the ratios of geometrical and arithmetical means of end-vertex degrees of edges

TL;DR: The geometrical arithmetic index (GA) as discussed by the authors is a topological index based on the end-vertex degrees of edges and its basic features are presented in this paper.
Journal ArticleDOI

On a novel connectivity index

TL;DR: In this paper, the sum-connectivity index for molecular graphs is proposed and several basic properties for this index, especially lower and upper bounds in terms of graph (structural) invariants.
References
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Book

Applied Regression Analysis

TL;DR: In this article, the Straight Line Case is used to fit a straight line by least squares, and the Durbin-Watson Test is used for checking the straight line fit.
Book

Handbook of Molecular Descriptors

TL;DR: This Users guide notations acronyms list of molecular descriptors contains abbreviations for molecular descriptor values that are useful for counting and topological descriptors calculation.
Journal ArticleDOI

Beware of q2

TL;DR: It is argued that the high value of LOO q2 appears to be the necessary but not the sufficient condition for the model to have a high predictive power, which is the general property of QSAR models developed using LOO cross-validation.