Predictive modeling of asthma drug properties using machine learning and topology indexes in MATLAB-based QSPR research

Machine Learning


  • ong, Ky Whats New Asthma 2018 Report and subsequent global initiatives. Allergo J. int. 2863–72 (2019).

    MathScinet Google Scholar

  • Mims, J. W. (2015). Asthma: Definition and pathophysiology. International Forum for Allergies and Nose (Vol. 5, No. S1, pp. S2-S6).

  • Patadia, Missouri, Marrill, LL & Corey, J. Asthma: Symptoms and symptoms. Otolaryngol. Clean. North AM. 47(1), 23–32 (2014).

    PubMed Google Scholar

  • Krishnan, JA, et al. Asthma outcome: Symptoms. J. Allergy cleans. Imnor. 129(3), S124 – S135 (2012).

    PubMed PubMed Central Google Scholar

  • Thailand, A. Etal. Results of childhood asthma up to age 50. J. Allergy cleans. Imnor. 133(6), 1572–1578 (2014).

    PubMed Google Scholar

  • Douwes, J., Boezea, M. , and Pearce, N. (2009). Chronic obstructive pulmonary disease and asthma. Oxford Public Health Textbook, Vol. 3: Practice of Public Health (ed. 5), 1021-1045.

  • To, T. et al. Global prevalence of asthma in adults: results from a cross-sectional global health survey. BMC Public Health 12(1), 1–8 (2012).

    Google Scholar

  • Anderson, HR is the prevalence of asthma changes. arch. dis. child. 64(1), 172 (1989).

    PubMed PubMed Central CAS Google Scholar

  • Magnus, P. & Jaakkola, JJ Secular Trends Secular Trends in the outbreak of asthma among children and young adults: a key assessment of repeated cross-sectional surveys. BMJ 314(7097), 1795 (1997).

    PubMed PubMed Central CAS Google Scholar

  • Mekenyan, O., Bonchev, D., Sabljic, A. & Trinajstic, N. Application of topology index to electropy indexes for the use of the Balaban index and correlation with mouse ether toxicity. Acta Charmaceutica Jugoslavica 37(1), 75–86 (1987).

    CAS Google Scholar

  • Estrada, E. & Uriarte, E. Recent advances in the role of topology indexes in drug discovery research. Curr. Pharmaceuticals. Chemistry. 8(13), 1573–1588 (2001).

    PubMed CAS Google Scholar

  • S. C., Mills, D., Gute, B. D., Grunwald, G. D., & Balaban, (2002). Application of topology indexes in chemical properties/biological activity/toxicity prediction. Chemistry Topology (pp. 113-184). Woodhead Publishing.

  • Pyka, A. Application of topology indexes for prediction of the biological activity of selected alkoxyphenols. Acta pol. Drug. 59(5), 347–352 (2002).

    PubMed CAS Google Scholar

  • Natarajan, R., Kamalakanan, P. , & Nirdosh, I. (2003). Application of topological indicators to structural activity relationship modeling and mineral collector selection.

  • Mahboobob, A., Rasheed, M.W., Bayati, J.H., & Hanif, I. (2023). Some Banhatti calculations and revenue immutable silicon carbide. Baghdad Science Journal, 20 (3 (suppl.)), 1099-1099.

  • Hussein Bayati, J.H., Mahboob, A. , and Rasheed, M. W. (2024). Abid-Waheed partition dimensions and domination \((aw)_ {r}^{s} \) graph. Baghdad Science Journal, 21 (5).

  • Balasubramaniyan, D. & Chidambaram, N. EUR. Phys. J. Plus 138(9), 823 (2023).

    CAS Google Scholar

  • Arockiaraj, M., Campena, F.J.H., Greeni, A.B., Ghani, Mu, Gajavalli, S., Tchier, F. , & Jan, A. Z. (2024). QSPR analysis of distance-based structural index of drug compounds in the treatment of tuberculosis. Helyon, 10 (2).

  • Mahboobob, A., Rasheed, M.W., Dhiaa, Am, Hanif, I. , &Amin, L. (2024). Analysis of physicochemical properties and antihepatitis prescription drugs using quantitative structure-property relationship (QSPR) linear regression model. Helyon.

  • Hasani, M. &Ghods, M. Topological index and QSPR analysis of several chemical structures applied to the treatment of cardiac patients. int. J. Quantum Chem. 124(1), E27234 (2024).

    Google Scholar

  • Kirana, B., Shanmukha, M. C., and Usha, A. (2024). QSPR analysis and curve regression of varying degree-based topology indexes of quinolone antibiotics.

  • Huang, S., Xu, P. & Liu, Y. Mass spectrometry-based metabolomics machine learning application. anus. T-m. ACTA 9141–13 (2016).

    Google Scholar

  • Cheng, F., Li, W., Liu, G. & Tang, Y. Machine learning and chemistry-informatics approaches for drug discovery. Chemistry. Pastor 112(1), 379–434 (2012).

    Google Scholar

  • Lavecchia, A. Machine learning approaches in drug discovery: methods and applications. Drug discov. today 20(3), 318–331 (2015).

    PubMed Google Scholar

  • T. Chen and C. Guestrin, Xgboost: A scalable tree boost system, Proceedings of the International Conference on Knowledge Discovery and Data Mining on the 22nd ACM SIGKDD International Conference, pp. 785-794, 2016.

  • Lo, Y.-C., Rensi, SE, Torng, W. &Altman, Comparative analysis of machine learning algorithms for QSPR modeling of RB solubility. J. Chem. Inf. Model. 60(4), 1714–1723 (2020).

    Google Scholar

  • Gutman, I. , and Trinajstic, N. (1972). Graph theory and molecular orbitals. Total F-electron energy of alternative hydrocarbons. Chemical Physics Letters, 17(4), 535-538.

  • Xu, K. Zagreb index of a graph with a specific creek number. Appl. Mathematics. Rhett. twenty four(6), 1026–1030 (2011).

    MathScinet Math Google Scholar

  • Islam, SR & PAL, M. The second Zagreb index of fuzzy graphs and its application in mathematical chemistry. J. Fazzy Sight from Iran. 20(1), 119–136 (2023).

    MathScinet Google Scholar

  • Mahboobob, A., Rasheed, M.W., Amin, L. & Hanif, I. Study of novel molecular descriptors and quantitative structure and overperty relationship analysis of hematological cancer drugs. EUR. Phys. J. Plus 138(9), 856 (2023).

    CAS Google Scholar

  • Randic, M. Characterization of molecular branching. J. Am. Chemistry. Soc. 97(23), 6609–6615 (1975).

    CAS Google Scholar

  • Du, Z., Jahanbai, A. & Sheikholeslami, relationship between SM Randic Index and other topological indices. commune. Perfect combination. 6(1), 137–154 (2021).

    MathScinet Math Google Scholar

  • Computational and analytical studies of the Randic Index of Martinez-Martinez, CT, Mendez-Bermudez, JA, Rodriguez, JM & Sigarreta, JM Erdos-Renyi models. Appl. Mathematics. computer. 377125137 (2020).

    MathScinet Math Google Scholar

  • Ediza, S. Etal. Notes on total Zagreb QSPR analysis and total disease index of octane. Eurasian chemical communication. 3139–45 (2021).

    Google Scholar

  • Shirdel, GH, Rezapour, H. , and Sayadi, Am (2013). Hyper-Zagreb index for graph manipulation.

  • Suresh, M. , and Devi, G. S. (2020, November). Some operations of the Hyper-Zagreb index. Proceedings of the AIP Conference (Vol. 2277, No. 1, p. 140003). AIP Publishing LLC.

  • Zhou, H., Mahboob, A., Rasheed, M. W., Ovais, A., Siddiqui, M. K., & Cheema, IZ (2023). QSPR analysis of molecular descriptors and thermodynamic features of narcotics. Polycyclic aromatic compounds, 1-21.

  • Shanmukha, MC, Basavarajappa, NS, Shilpa, KC, & Usha, A. (2020). Degree-based topology index for anticancer drugs with QSPR analysis. Helyon, 6 (6).

  • Reti, T. For some characteristics of graph irregularity indexes that are particularly respected by S-Index. Appl. Mathematics. computer. 344107–115 (2019).

    MathScinet Google Scholar

  • Furtula, B. & Gutman, I. Forgotten topology index. J. Mathematics. Chemistry. 53(4), 1184–1190 (2015).

    MathScinet CAS Math Google Scholar

  • Mondal, S. & Das, KC's degree-based graph StructureProperty modeling entropy. entropy twenty five(7), 1092 (2023).

    ADS PubMed PubMed Central CAS Google Scholar

  • Kulli, VR Grava's index and graph cooperative. Anne. Pure Appl. Mathematics. 14(1), 33–38 (2017).

    Google Scholar

  • Kulli, Gourava index for VR status graphs. International Journal of Recent Scientific Research, 11(1), 36770-36773.



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