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  1. Article ; Online: Comparative Study of Planar Octahedron Molecular Structure via Eccentric Invariants.

    Chu, Zheng-Qing / Ali, Haidar / Ali, Didar Abdulkhaleq / Nadeem, Muhammad / Kirmani, Syed Ajaz K / Ali, Parvez

    Molecules (Basel, Switzerland)

    2023  Volume 28, Issue 2

    Abstract: A branch of graph theory that makes use of a molecular graph is called chemical graph theory. Chemical graph theory is used to depict a chemical molecule. A graph is connected if there is an edge between every pair of vertices. A topological index is a ... ...

    Abstract A branch of graph theory that makes use of a molecular graph is called chemical graph theory. Chemical graph theory is used to depict a chemical molecule. A graph is connected if there is an edge between every pair of vertices. A topological index is a numerical value related to the chemical structure that claims to show a relationship between chemical structure and various physicochemical attributes, chemical reactivity, or, you could say, biological activity. In this article, we examined the topological properties of a planar octahedron network of
    Language English
    Publishing date 2023-01-05
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 1413402-0
    ISSN 1420-3049 ; 1431-5165 ; 1420-3049
    ISSN (online) 1420-3049
    ISSN 1431-5165 ; 1420-3049
    DOI 10.3390/molecules28020556
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.MO 81: Show issues

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  2. Article ; Online: Study for Some Eccentricity-based Topological Indices of Second Type of Dominating David-derived Network.

    Liu, Jia-Bao / Ali, Haidar / Ali, Didar Abdulkhaleq / Umer, Ayesha / Ali, Parvez / Kirmani, Syed Ajaz K

    Combinatorial chemistry & high throughput screening

    2023  

    Abstract: Background: Dominating David-derived networks are widely studied due to their fractal nature, with applications in topology, chemistry, and computer sciences. The use of molecular structure descriptors is a standard procedure that is used to correlate ... ...

    Abstract Background: Dominating David-derived networks are widely studied due to their fractal nature, with applications in topology, chemistry, and computer sciences. The use of molecular structure descriptors is a standard procedure that is used to correlate the biological activity of molecules with their chemical structures, which can be useful in the field of pharmacology.
    Objective: This article's goal is to develop analytically closed computing formulas for eccentricity-based descriptors of the second type of dominating David-derived derived network. Thermodynamic characteristics, physicochemical properties, and chemical and biological activities of chemical graphs are just a few of the many properties that may be determined using these computation formulas.
    Methods: Vertex sets were initially divided according to their degrees, eccentricities, and cardinalities of occurrence. The eccentricity-based indices are then computed using some combinatorics and these partitions.
    Results: Total eccentricity, average eccentricity, and the Zagreb index are distance-based topological indices utilized in this study for the second type of dominating David-derived network, denoted as D_2 (m).
    Conclusion: These calculations will assist the readers in estimating the fractal and difficult-to-handle thermodynamic and physicochemical aspects of chemical structure. Apart from configuration and impact resistance, the D_2 (m) design has been used for fundamental reasons in a variety of technical and scientific advancements.
    Language English
    Publishing date 2023-08-31
    Publishing country United Arab Emirates
    Document type Journal Article
    ZDB-ID 2064785-2
    ISSN 1875-5402 ; 1386-2073
    ISSN (online) 1875-5402
    ISSN 1386-2073
    DOI 10.2174/1386207326666230831125646
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5577: Show issues Location:
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    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  3. Article ; Online: Breast cancer chemical structures and their partition resolvability.

    Huang, Qingqun / Khalil, Adnan / Ali, Didar Abdulkhaleq / Ahmad, Ali / Luo, Ricai / Azeem, Muhammad

    Mathematical biosciences and engineering : MBE

    2022  Volume 20, Issue 2, Page(s) 3838–3853

    Abstract: Cancer is a disease that causes abnormal cell formation and spreads throughout the body, causing harm to other organs. Breast cancer is the most common kind among many of cancers worldwide. Breast cancer affects women due to hormonal changes or genetic ... ...

    Abstract Cancer is a disease that causes abnormal cell formation and spreads throughout the body, causing harm to other organs. Breast cancer is the most common kind among many of cancers worldwide. Breast cancer affects women due to hormonal changes or genetic mutations in DNA. Breast cancer is one of the primary causes of cancer worldwide and the second biggest cause of cancer-related deaths in women. Metastasis development is primarily linked to mortality. Therefore, it is crucial for public health that the mechanisms involved in metastasis formation are identified. Pollution and the chemical environment are among the risk factors that are being indicated as impacting the signaling pathways involved in the construction and growth of metastatic tumor cells. Due to the high risk of mortality of breast cancer, breast cancer is potentially fatal, more research is required to tackle the deadliest disease. We considered different drug structures as chemical graphs in this research and computed the partition dimension. This can help to understand the chemical structure of various cancer drugs and develop formulation more efficiently.
    MeSH term(s) Female ; Humans ; Breast Neoplasms/genetics ; Antineoplastic Agents/therapeutic use ; Signal Transduction ; Risk Factors
    Chemical Substances Antineoplastic Agents
    Language English
    Publishing date 2022-12-12
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2265126-3
    ISSN 1551-0018 ; 1551-0018
    ISSN (online) 1551-0018
    ISSN 1551-0018
    DOI 10.3934/mbe.2023180
    Database MEDical Literature Analysis and Retrieval System OnLINE

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