Sentence examples for predictive interaction from inspiring English sources

We also noted that within this group of interactions the markers did not represent those selected based on predictive interaction effects using main effect or an algorithm that predict involvements SNP-SNP interactions.

In this way interpretable and predictive interaction models are created that are able to generalize to new protein-ligand combinations, and to new proteins and new ligands [17].

An overview on correlational and predictive interaction of sensory function, pain, hyperalgesia, and motor and psychological functioning is depicted in Figure 7. Chronic CRPS was characterized by chronic pain at rest and during exercise, combined with substantially limited hand force and impaired motor function.

Such GSP set was used to score the interaction network and to assign each predictive interaction pair with quantitative measurements.

For instance, our predictive interaction pair, AT2G33210 and AT2G39770, has corresponding interaction pair, NP_418567.1 and NP_416543.1, in E.coliK12, which has been confirmed by the pull down experiment [ 33].

We built and calibrated a predictive interaction model using single-chemical exposure data to obtain enzymatic microconstant values for benzene, toluene, ethylbenzene, and m-xylene individually.

Such predictive interactions are essential for the perspective of further development of designing strategies and safe usage of nanomaterials [53 55].

We obtained a network composed of 2913 nodes as 5′UTR mRNAs and 6705 edges modeling the predictive interactions.

The interaction search was restricted to Homo Sapiens and includes all kind of experimental procedure as well as some predictive interactions (mainly from the OPHID database).

Engaging in play could provide the developing brain with spatially and temporally predictive interactions with the outside world and thereby tune the developing network's ability to select which information to attend to when, and which information to ignore.

The regression framework assumes that the outcome Y is a linear function of prognostic covariates, X1; putative predictive biomarkers, X2; the treatment indicator, A; and treatment-by-predictive interaction, AX2: (4) μ A, X = E (Y   ∣   A, X ) = β 0 + β 1 X 1 + β 2 X 2 + A β 3 + β 4 X 2. Let Δ(X) = E(Y∣ A = 1, X) − E(Y∣ A = 0, X) = μ(A = 1, X) − μ(A = 0, X) denote the treatment contrast.