The article is devoted to investigate the dynamics of behavior of functional-differential equation with delay of mathematical model of the regulatory mechanisms of cardiac activity and liver function in pathogenesis. Moreover, the results of the computational experiment for the quantitative analysis of the object state are presented. The behavior of the system in the zone of dynamic chaos was analyzed with the use of developed software.

To predict the spread of the new coronavirus infection COVID-19, the critical values of spread indicators have been determined for deciding on the introduction of restrictive measures using the city of Moscow as an example. A model was developed using classical methods of mathematical modeling based on exponential regression, the accuracy of the forecast was estimated, and the shortcomings of mathematical methods for predicting the spread of infection for more than two weeks. As a solution to the problem of the accuracy of long-term forecasts for more than two weeks, two models based on machine learning methods are proposed: a recurrent neural network with two layers of long short-term memory (LSTM) blocks and a 1-D convolutional neural network with a description of the choice of an optimization algorithm. The forecast accuracy of ML models was evaluated in comparison with the exponential regression model and one another using the example of data on the number of COVID-19 cases in the city of Moscow.

The article is devoted to investigate the dynamics of the regulatory mechanisms of viral miRNA during oncogenesis at Hepatitis B virus infection. Studies show that mutually conjugated molecular-genetic systems of hepatocytes and micro-RNA of oncogenic viruses have the following domains: a stable functional activity, the possibility of oscillatory modes of functioning, irregular oscillations (it may occur the chaotic behavior of oncoviruses micro-RNA and their regulatory network connections, which leads to chaotic uncontrolled cellular reproduction and cancer) and black hole effect (sharp reduction in the number of cells, which corresponds to the metastasis of cancer cells). The results of computational experiments show that depending on the parameters of the cell and the cellular external environment, some miRNAs can both activate and inhibit tumor growth.

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