This network analysis approach has potential applications to a diverse body of biological data, for example, protein complex prediction, functional prediction, gene variation, and regulatory interactions.
As shown in Table S1, Case 2 is associated with negative estimates of the biophysical parameter αx (with αe = 0 fixed), which is found to be contributing to the high sensitivities of the model predictions to variation in matrix [Ca2+] and stiff gradients of Ca2+ uptake profiles to variation in ΔΨ.
In addition, Case 2 was associated negative estimates of the biophysical parameter αx (with αe = 0 fixed) (Table S1), attributing to the high sensitivities of the model predictions to variation in matrix [Ca2+] (Figure 1(D F): lower panel) and stiff gradients of Ca2+ uptake profiles to variation in ΔΨ (Figure 2 (D F): lower panel).
We tested these predictions using variation in randomly amplified polymorphic DNA.
Predictions of variation in frequency range and sensitivity to measurement errors are made based on the behaviour of the determinant of the transformation matrix, and are verified by simulation.
Furthermore, the Case 2 is associated with negative estimates of the biophysical parameter αx (with αe = 0 fixed) (see Table S1), which is found to be contributing to the high sensitivities of the model predictions to variation in matrix [Ca2+].
Preoperative and postoperative LOS predictions exhibit variation and are not symmetrically distributed around the regression line.
Contour plots were produced to assess the response of mean annual and long-term species richness predictions to variation in m and d.
Also, some of the most recent data and theoretical predictions link variation in those traits with different fitness components [ 1, 2, 6].
The next-generation RB model that incorporates the RBW model will have an important impact on the global radiation belt modeling that is expected to improve prediction of variation in radiation belt electron flux.
