Example 2
A dataset of variability patterns at the cellular levels is generated using several single cell-based techniques. Assessments of single cell variabilities in gene expression are performed using single cell RNA sequencing; single cell proteomics; single cell metabolomics; single cell epitopes expression and cytokine secretion. Cell are harvested from patients before and after chronic disease therapy. The results are incorporated into a database. A method for quantifying the variability patterns is selected, based for example on methods for quantifying nonlinear or chaotic systems; methods for quantifying entropy; use of ratios between two consecutive measurements; mean of ratios of variabilities between two or more consecutive measurements; sample entropy algorithm; complexity index; multiscale entropy measurements; and any type of combinations of methods, which are used for signifying variability pattern(s). The resulting number(s)/factor(s), which are generated by using one or more of these methods are implemented into operating systems for improving their function and for reaching a pre-determined goal.
