New topology indices that are degree-based have been introduced to represent molecular
structure from chemical graph theory. The indices give a new sight into the physical …

A novel framework for inverse quantitative structure–activity relationships (inverse QSAR)
has recently been proposed and developed using both artificial neural networks and mixed …

Abstract Analysis of chemical graphs is becoming a major research topic in computational
molecular biology due to its potential applications to drug design. One of the major …

Inference of chemical compounds with desired properties is important for drug design,
chemo-informatics, and bioinformatics, to which various algorithmic and machine learning …

From the initial steps of early drug discovery, the traditional techniques, like docking, QSAR,
or molecular dynamics, have been used for decades identifying targets, ranking molecule …

Drug discovery is one of the major goals of computational biology and bioinformatics. A
novel framework has recently been proposed for the design of chemical graphs using both …

A novel framework has recently been proposed for designing the molecular structure of
chemical compounds with a desired chemical property using both artificial neural networks …

Recently a novel framework has been proposed for designing the molecular structure of
chemical compounds using both artificial neural networks (ANNs) and mixed integer linear …

The maximum number of edges in a graph with matching number m and maximum degree d
has been determined in Chvátal and Hanson (1976) and Balachandran and Khare (2009) …

In this paper, we propose a novel family of descriptors of chemical graphs, named cycle-
configuration (CC), that can be used in the standard" two-layered (2L) model" of mol-infer, a …