Finite vertex-based resolvability of supramolecular chain in dialkyltin

Zhang, Xiujun; Kanwal, Muhammad Tanzeel Ali; Azeem, Muhammad; Jamil, Muhammad Kamran; Mukhtar, Muzammil

doi:10.1515/mgmc-2022-0027

Cited by 8 publications

(4 citation statements)

References 33 publications

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“…However, it suffers from problems such as low computational efficiency as the data volume grows. Therefore, representing the semantic information in medical entities as dense low-dimensional real-valued vector methods will be the next research direction [33,34]; (c) The scale of data is still not large enough, although the types of data in this study are diverse. For the DIK architecture to collect richer and more accurate information from the data, the data scale needs to be further expanded in future work [35,36]; (d) The imperfection of the architecture of DIK.…”

Section: Discussionmentioning

confidence: 99%

Research on Hierarchical Knowledge Graphs of Data, Information, and Knowledge Based on Multiple Data Sources

Liu

et al. 2023

Applied Sciences

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In the existing medical knowledge graphs, there are problems concerning inadequate knowledge discovery strategies and the use of single sources of medical data. Therefore, this paper proposed a research method for multi-data-source medical knowledge graphs based on the data, information, knowledge, and wisdom (DIKW) system to address these issues. Firstly, a reliable data source selection strategy was used to assign priorities to the data sources. Secondly, a two-step data fusion strategy was developed to effectively fuse the processed medical data, which is conducive to improving the quality of medical knowledge graphs. The proposed research method is for the design of a multi-data-source medical knowledge graph based on the DIKW system. The method was used to design a set of DIK three-layer knowledge graph architectures according to the DIKW system in line with the medical knowledge discovery strategy, employing a scientific method for expanding and updating knowledge at each level of the knowledge graph. Finally, question and answer experiments were used to compare the two different ways of constructing knowledge graphs, validating the effectiveness of the two-step data fusion strategy and the DIK three-layer knowledge graph.

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Section: Discussionmentioning

confidence: 99%

Research on Hierarchical Knowledge Graphs of Data, Information, and Knowledge Based on Multiple Data Sources

Liu

et al. 2023

Applied Sciences

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“…There are certain methodologies, such as QSAR, QSPR, and QSTR, in which chemists or pharmacists use drug-related data, such as melting point, boiling point, molar refractivity, flash point, and complexity for further research and the design of novel medications. − QSPR analysis provides a systematic method for understanding the characteristics of pharmaceuticals that contribute to their efficacy in targeting specific aspects of the disorder. The selection of drugs for quantitative structure–property relationship (QSPR) analysis employing topological indices takes into account both the drugs′ characteristics and the desired properties.…”

Section: Methodsmentioning

confidence: 99%

QSPR Analysis of Drugs for Treatment of Schizophrenia Using Topological Indices

Zhang,

Saif,

Idrees

et al. 2023

ACS Omega

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Schizophrenia is a chronic psychotic disorder characterized primarily by cognitive deficits. Drugs and therapies are helpful in managing the symptoms, mostly with long-term compliance. There is a pressing need to design more efficient drugs with fewer adverse effects. Solubility, metabolic stability, toxicity, permeability, and transporter effects are important parameters in the efficacy of drug design, which in turn depend upon different physical and chemical characteristics of drugs. In recent years, there has been growing interest in developing computational tools for the discovery and development of drugs for schizophrenia. Some of these methods use machine learning algorithms to predict the efficacy and side effects of the potential drugs. Other studies have used computer simulations to understand the molecular mechanisms underlying the disease and identify new targets for drug development. Topological indices are numeric quantities linked to the chemical structure of drugs and predict the properties, reactivity, and stability of drugs through the quantitative structure−property relationship (QSPR). This work is aimed at using statistical techniques to link QSPR correlating properties with connectivity indices using linear regression. The QSPR model gives quite a better estimation of the properties of drugs, such as melting point, boiling point, enthalpy, flash point, molar refractivity, refractive index, complexity, molecular weight, and refractivity. Results are validated by comparing actual values to estimated values for the drugs.

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“…Explicit formulas for the expected values of certain degree-based topological descriptors of random phenylene chains were provided by Hui et al (Hui et al, 2023). Zhang et al (Zhang et al, 2018), discussed the topological indices of generalized bridge molecular graphs, while in separate works (Zhang et al, 2022;Zhang et al, 2023), they computed the topological indices of some supramolecular chains using graph invariants. For more details on this topic of research, readers can see the following papers (Mondal et al, 2019;Xu et al, 2020;Mondal et al, 2021;Raza, 2021).…”

Section: R G ( )mentioning

confidence: 99%

Analyzing the expected values of neighborhood degree-based topological indices in random cyclooctane chains

Jing,

Yousaf,

Farhad

et al. 2024

Front. Chem.

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Cyclooctane is classified as a cycloalkane, characterized by the chemical formula C8H16. It consists of a closed ring structure composed of eight carbon atoms and sixteen hydrogen atoms. A cyclooctane chain typically refers to a series of cyclooctane molecules linked together. Cyclooctane and its derivatives find various applications in chemistry, materials science, and industry. Topological indices are numerical values associated with the molecular graph of a chemical compound, predicting certain physical or chemical properties. In this study, we calculated the expected values of degree-based and neighborhood degree-based topological descriptors for random cyclooctane chains. A comparison of these topological indices’ expected values is presented at the end.

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Finite vertex-based resolvability of supramolecular chain in dialkyltin

Cited by 8 publications

References 33 publications

Research on Hierarchical Knowledge Graphs of Data, Information, and Knowledge Based on Multiple Data Sources

Research on Hierarchical Knowledge Graphs of Data, Information, and Knowledge Based on Multiple Data Sources

QSPR Analysis of Drugs for Treatment of Schizophrenia Using Topological Indices

Analyzing the expected values of neighborhood degree-based topological indices in random cyclooctane chains

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