对数回归模型对铌酸铽拓扑指标和熵测度的综合研究

IF 3.1 4区生物学 Q2 BIOLOGY

Computational Biology and Chemistry Pub Date : 2025-07-10 DOI:10.1016/j.compbiolchem.2025.108558

W. Eltayeb Ahmed , Muhammad Farhan Hanif , Mazhar Hussain , Muhammad Kamran Siddiqui

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引用次数: 0

摘要

本文从化学图论的角度对铌酸铽（TbNbO4）的分子图进行了详细的数学研究。计算了一系列基于度的拓扑指数，如randiski， ABC， GA， Zagreb及其重新定义的版本，以定义分子结构。此外，从这些指标中找到相关的熵值来确定结构复杂性和信息含量。数值和图形研究说明了指数和熵如何与分子大小相关，显示出独特的增长趋势和敏感性。对数SPSS回归模型的制定，以调查如何拓扑指数是相关的熵措施，提供显著的相关性。这些发现表明，不同的指数在表示局部和全局结构方面是如何相互补充的，并且在分子表征、药物发现和计算化学中是有用的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

A comprehensive study on topological indices and entropy measures for terbium niobate using logarithmic regression models

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A comprehensive study on topological indices and entropy measures for terbium niobate using logarithmic regression models

In this article, we establish a detailed mathematical investigation of the molecular graph of terbium niobate (TbNbO

_{4}

) from a chemical graph theory point of view. A series of degree-based topological indices, such as Randić, ABC, GA, Zagreb, and their redefined versions, are calculated to define molecular structure. In addition, related entropy values from these indices are found to determine structural complexity and information content. Numerical and graphical studies illustrate how indices and entropies are related to molecular size, showing unique growth trends and sensitivities. Logarithmic SPSS regression models are formulated to investigate how topological indices are related to entropy measures, providing significant correlations. The findings show how various indices are complementary to each other in representing local and global structures and are useful in molecular characterization, drug discovery, and computational chemistry.

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来源期刊

Computational Biology and Chemistry 生物-计算机：跨学科应用

CiteScore

6.10

自引率

3.20%

发文量

142

审稿时长

24 days

期刊介绍： Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.