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Compressed graph representation for scalable molecular graph generation [PDF]

open access: yesJournal of Cheminformatics, 2020
Recently, deep learning has been successfully applied to molecular graph generation. Nevertheless, mitigating the computational complexity, which increases with the number of nodes in a graph, has been a major challenge. This has hindered the application
Youngchun Kwon   +4 more
doaj   +2 more sources

Group graph: a molecular graph representation with enhanced performance, efficiency and interpretability [PDF]

open access: yesJournal of Cheminformatics
The exploration of chemical space holds promise for developing influential chemical entities. Molecular representations, which reflect features of molecular structure in silico, assist in navigating chemical space appropriately.
Piao-Yang Cao   +5 more
doaj   +2 more sources

Efficient learning of non-autoregressive graph variational autoencoders for molecular graph generation [PDF]

open access: yesJournal of Cheminformatics, 2019
With the advancements in deep learning, deep generative models combined with graph neural networks have been successfully employed for data-driven molecular graph generation.
Youngchun Kwon   +5 more
doaj   +2 more sources

The high-energy band in the photoelectron spectrum of alkanes and its dependence on molecular structure [PDF]

open access: yesJournal of the Serbian Chemical Society, 1999
In the model for the ionization energies of the C2s-electrons in saturated hydrocarbons, put forward by Heilbronner et al., the energy levels are calculated as eigenvalues of the line graph of the hydrogen-filled molecular graph. It is now shown
Gutman Ivan   +3 more
doaj   +3 more sources

Degree-Based Graph Entropy in Structure–Property Modeling

open access: yesEntropy, 2023
Graph entropy plays an essential role in interpreting the structural information and complexity measure of a network. Let G be a graph of order n. Suppose dG(vi) is degree of the vertex vi for each i=1,2,…,n.
Sourav Mondal, Kinkar Chandra Das
doaj   +1 more source

Prediction of Drug-Drug Interaction Using an Attention-Based Graph Neural Network on Drug Molecular Graphs

open access: yesMolecules, 2022
The treatment of complex diseases by using multiple drugs has become popular. However, drug-drug interactions (DDI) may give rise to the risk of unanticipated adverse effects and even unknown toxicity.
Yue-Hua Feng, Shao-Wu Zhang
doaj   +1 more source

User's interface for extraction of the chemical structure information from the systematic name of organic compound

open access: yesСистемный анализ и прикладная информатика, 2023
The user's interface «Nomenclature Generator» for extraction of the chemical structure information from the systematic name of organic compound represented according to IUPAC nomenclature is developed at the All-Russian Institute for Scientific and ...
L. A. Grigoryan
doaj   +1 more source

An estimation of HOMO–LUMO gap for a class of molecular graphs

open access: yesMain Group Metal Chemistry, 2022
For any simple connected graph G of order n, having eigen spectrum μ 1 ≥ μ 2 ≥ ⋯ ≥ μ n with middle eigenvalues μ H and μ L, where H = ⌊(n + 1)/2⌋ and L = ⌈(n + 1)/2⌉, the HOMO ...
Hameed Saira   +3 more
doaj   +1 more source

Relating Estrada index with spectral radius [PDF]

open access: yesJournal of the Serbian Chemical Society, 2007
The Estrada index EE is a recently proposed molecular structure-descriptor, used in the modeling of certain features of the 3D structure of organic molecules, in particular of the degree of folding of proteins and other long-chain biopolymers.
IVAN GUTMAN   +4 more
doaj   +3 more sources

A graph theoretical approach to cis/trans isomerism [PDF]

open access: yesJournal of the Serbian Chemical Society, 2014
A simple graph-theory-based model is put forward, by means of which it is possible to express the energy difference between geometrically non-equivalent forms of a conjugated polyene.
Furtula Boris   +2 more
doaj   +1 more source

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