This spectrum is in clear disagreement with the form given by the statistical expression.
In this respect, we note that over the same cap satellite-based magnetic field models more recent than MF6 (Maus et al. 2008) e.g., MF7, GRIMM (Lesur et al. 2013), CM5 (Sabaka et al. 2015) are more energetic over the same bandwidth, although still less energetic than predicted by the statistical expression.
By a misfit analysis between the regional power spectrum, as described by Eqs. 10 and 11 and the statistical expression of Eq. 19 it is possible to carry out regional analyses and estimate for any spherical cap the mean magnetization and the mean magnetic thickness.
For most such cases (77/121 or 64% genes), the tissue showing equal expression also had lower coverage, suggesting that some of these disagreements may be false positives caused by the statistical difficulty in confirming differential expression of homoeoloci for genes expressed at low levels.
We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results.
We aim to develop a new molecular thermodynamic model for predicting the surface thermodynamic properties of pure ionic liquids (ILs) based on the statistical mechanical expression developed by Winterfeld et al. (1978. AIChE. J. 24, 1010).
A novel analysis framework, implemented in the R package FunPat, was developed to search for the main temporal patterns in classes of functional Gene Sets and to improve the gene selection by integrating the statistical evidence of differential expression with the information on the temporal profiles and the functional annotations.
A novel analysis pipeline was developed to search the main temporal patterns in classes of genes similarly annotated, improving the sensitivity of gene selection by integrating the statistical evidence of differential expression with the information on temporal profiles and the functional annotations.
The edges are scored by the Fisher's method by combining the statistical significance p-values of differential expression and co-expression.
By combining data from multiple expression studies, analyses of gene expressions have the statistical power to detect even small differences in gene expression between normal and tumor tissues.
Given a data set of reported cases I(t i ), i = 1,2,…, k at times t i, we consider a sliding window of n consecutive reports I(t i ) to compare the statistical models defined by expressions (4) and (5).
