paper-with-me

Papers

Vertex-Edge Weighted Molecular Graphs: A study on topological indices and their relevance to physicochemical properties of drugs in use cancer treatment

2024-07-28 · Sezer Sorgun, Kahraman Birgin

Quantitative Structure-Property Relationship (QSPR) analysis plays a crucial role in predicting physicochemical properties and biological activities of pharmaceutical compounds, aiding in drug design and optimization. This study focuses on leveraging QSPR within the framework of vertex and edge weighted (VEW) molecular graphs, exploring their significance in drug research. By examining 48 drugs in used in the treatment of various cancers and their physicochemical properties, previous studies serve as a foundation for our research. Introducing a novel methodology for computing vertex and edge weights, exemplified by the drug Busulfan, we highlight the importance of considering atomic properties and inter-bond dynamics. Statistical analysis, employing linear regression models, reveals enhanced correlations between topological indices and physicochemical properties of drugs. Comparison with previous studies on unweighted molecular graphs highlights the enhancements achieved with our approach.

📄 PDF Abstract BibTeX arXiv:2408.06367

Code (0)

등록된 구현이 없습니다.

Tasks

Drug Design

Methods 이 논문이 사용한 방법론

Linear Regression Linear Regression is a method for modelling a relationship between a dependent variable and independent variables. These models can be fit with numerous approaches. The most…

Similar Papers 제목 키워드 기반

Geometric learning of the conformational dynamics of molecules using dynamic graph neural networks

2021-06-24 · Michael Hunter Ashby, Jenna A. Bilbrey

We apply a temporal edge prediction model for weighted dynamic graphs to predict time-dependent changes in molecular structure. Each molecule is represented as a complete graph in which each atom is a vertex and all vert…

Graph Neural Network

Cheeger Inequalities for Directed Graphs and Hypergraphs Using Reweighted Eigenvalues

2022-11-17 · Lap Chi Lau, Kam Chuen Tung, Robert Wang

We derive Cheeger inequalities for directed graphs and hypergraphs using the reweighted eigenvalue approach that was recently developed for vertex expansion in undirected graphs [OZ22,KLT22,JPV22]. The goal is to develop…

Exact Learning of Weighted Graphs Using Composite Queries

2025-11-18 · Michael T. Goodrich, Songyu Liu, Ioannis Panageas arxiv

In this paper, we study the exact learning problem for weighted graphs, where we are given the vertex set, $V$, of a weighted graph, $G=(V,E,w)$, but we are not given $E$. The problem, which is also known as graph recons…

Testing Dependency of Weighted Random Graphs

2024-09-23 · Mor Oren, Vered Paslev, Wasim Huleihel

In this paper, we study the task of detecting the edge dependency between two weighted random graphs. We formulate this task as a simple hypothesis testing problem, where under the null hypothesis, the two observed graph…

Even vertex $ζ$-graceful labeling on Rough Graph

2022-08-23 · R. Nithya, K. Anitha

Rough graph is the graphical structure of information system with imprecise knowledge. Tong He designed the properties of rough graph in 2006[6] and following that He and Shi introduced the notion of edge rough graph[7].…