Keywords: Multidimensional Time Model for Probability Cumulative Function, single-cell transcriptomics, immunological synapse
Vaccination play an important role not only in different Control or Clinical Trials, but also in measures against such epidemics, as Ebola etc…, and therefore, is closely related to studies of immunology and of immunological synapse of cells. The new method can be applied to immunological synapse of cells along with noise models for single-cell transcriptomics. The new method is based on changes of Cumulative Distribution Function in relation to time change in sampling patterns. Multidimensional Time Model for Probability Cumulative Function can be reduced to finite-dimensional time model, which can be characterized by Boolean algebra for operations over events and their probabilities and index set for reduction of infinite dimensional time model to finite number of dimensions of time model considering also the fractal-dimensional time arising from alike supersymmetrical properties of probability. It is based on the properties of composition of Brownian motion processes applied through application of Boolean prime ideal theorem and Stone duality. This model through Cumulant Analysis, Theory of Associated Random Variables., and Time Series analysis can be extended to uncertainty quantification of complex computational models in different areas of sciences that can require calculation of 5-fold integrals and the like.