Such applications arise, for example, in experimental physics, where the data in question is generated by accelerators, and in simulation science, where the data is generated by supercomputers.
With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.
For example, in experimental environments, children initially reorient themselves mainly by using geometric information, while the ability to use landmark information develops later in life [36], [37].
For example, in Experimental Applications II and III, our analyses based on SWISS agreed with results found in the literature, such as Affymetrix having the best intersite reproducibility [23] and one lane of RNA-Seq being comparable to a single gene expression microarray [27].
For example, in experimental autoimmune uveitis, rodents immunized with retinal self-antigens develop autoimmunity targeted to the posterior eye [ 22– 22].
For example, in experimental models the transfer of regulatory cells can prevent arthritis [ 52], while the depletion of said cells results in accelerated disease [ 53].
For example, in experimental mice, brief exposure to light during the night rapidly increases the expression of the core clock genes Per1-2 and their protein products [ 15].
For example, in experimental liver fibrosis, the same macrophages producing TNFα and TGFβ1 during the inflammatory peak and that drove the disease pathogenesis were involved in tissue regeneration during the repair phase.
All of these approaches are inappropriate when the selective pressure is strong, as is frequently the case, for example, in experimental studies of microbe adaptation and for immune-escape and drug-resistant mutations in intrahost viral populations.
For example, in experimental models of diabetes, SGLT2 inhibition reduces oxidative stress and suppresses markers of inflammation and fibrosis, including nuclear factor κβ and collagen IV expression [ 53, 54].
