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Öğe Analysis coronavirus disease (COVID-19) model using numerical approaches and logistic model(Amer Inst Mathematical Sciences-Aims, 2020) Ahmed, Ayub; Salam, Bashdar; Mohammad, Mahmud; Akgul, Ali; Khoshnaw, Sarbaz H. A.The coronavirus disease (COVID-19) is a global health care problem that international efforts have been suggested and discussed to control this disease. Although, there are many researches have been conducted on the basis of the clinical data and recorded infected cases, there is still scope for further research due to the fact that a number of complicated parameters are involved for future prediction. Thus, mathematical modeling with computational simulations is an important tool that estimates key transmission parameters and predicts model dynamics of the disease. In this paper, we review and introduce some models for the COVID-19 that can address important questions about the global health care and suggest important notes. We suggest three well known numerical techniques for solving such equations, they are Euler's method, Runge-Kutta method of order two (RK2) and of order four (RK4). Results based on the suggested numerical techniques and providing approximate solutions give important key answers to this global issue. Numerical results may use to estimate the number susceptible, infected, recovered and quarantined individuals in the future. The results here may also help international efforts for more preventions and improvement their intervention programs. More interestedly, for both countries, Turkey and Iraq, the basic reproduction numbers R-0 have been reported recently by several groups, a research estimation by 9 April 2020 revealed that R-0 for Turkey is 7.4 and for Iraq is 3.4, which are noticeably increased from the beginning of the pandemic. In addition, on the basis of WHO situation reports, the new confirmed cases in Turkey on 11 April are 5138, and in Iraq on 29 May are 416, which can be counted as the peak value from the beginning of the disease. Thus, we investigate the forecasting epidemic size for Turkey and Iraq using the logistic model. It can be concluded that the suggested model is a reasonable description of this epidemic disease.Öğe Mathematical Model for the Ebola Virus Disease(Amer Scientific Publishers, 2018) Akgul, Ali; Khoshnaw, Sarbaz H. A.; Mohammed, Wali H.Mathematical modeling for epidemic models are important tools in systems biology. Studying the behavior of diseases models frequently needs some methods of model analysis. The suggested computational tools of model analysis here significantly play in calculating some numerical approximate solutions and also identifying critical model elements. The suggested mathematical model of Ebola virus diseases helps us for further studying and understanding the disease in many ways such as integrate experimental knowledge into a coherent picture, calculating model population of state variables provides suggestions for its future development and identifying critical model parameters in this study is another way to study the model practically and give some suggestions for future improvements of the disease. More interestingly, the results in this project will help international efforts to control the Ebola in countries in West Africa.Öğe Mathematical modeling for enzyme inhibitors with slow and fast subsystems(Taylor and Francis Ltd., 2020) Akgül, Ali; Khoshnaw, Sarbaz H. A.; Abdalrahman, Awder S.Mathematical modeling for biochemical enzyme inhibitor systems plays an important role in the systems of biology. Studying and analyzing the dynamical behavior for such models often need some techniques to obtain the model reduction. The well-known techniques of model reduction are suggested in order to divide the model equations into slow and fast subsystems. They are quasi steady-state approximation and quasi-equilibrium approximation. These techniques are great mathematical tools for simplifying model equations and identifying some analytical approximate solutions. In this work, we define mathematical models of enzyme inhibitors and suggest the model reduction approaches. We study two models as examples for enzyme inhibitors such as competitive inhibition and uncompetitive inhibition. Obtained results show that the suggested approaches are effective tools to minimize the number of elements and to find analytical approximate solutions. Accordingly, the idea of separating slow and fast equations will be applied for a wide range of complex enzyme inhibitor networks. © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the University of Bahrain.Öğe Minimizing cell signalling pathway elements using lumping parameters(Elsevier, 2020) Akgul, Ali; Khoshnaw, Sarbaz H. A.; Rasool, Hemn M.Many complex cell signaling pathway models contain a large number of state variables and parameters. Such models often require computational tools and techniques of model reduction to minimize the number of elements. Techniques of model reduction play an important role in var-ious theoretical and practical applications in systems biology. We introduce a model an approach of model reduction based on lumping of parameters. The suggested technique provides us a good step forward in minimizing model parameters for cell signaling pathways. The proposed technique is applied for the mathematical modeling of NF-kappa B signal transduction pathway. The number of parameters is reduced from 37 to 8. Some numerical simulations are computed for different initial values. Results provide a good agreement between the complete and the simplified model with a high degree of predictive accuracy. More interestingly, the suggested technique in this work could be used by biologists for simplifying the complexity of cell signaling pathways and identifying crit-ical model parameters. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
