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AgiMicroRna uses the linear model features implemented in the limma package to assess the differential expression between different experimental conditions and provides links to the miRBase for those microRNAs that have been declared as significant in the statistical analysis.
AgiMicroRna uses the linear model features implemented in the limma package [ 16] to fit a linear model to each microRNA, and thereby assesses the differential expression between different experimental conditions.
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Analytical solution for the problem of frictional-elastic collisions of spherical particles using the linear model.
Figure 7 presents product variation with cell growth and substrate consumption using the linear model and Fig. 8 using the exponential model.
We assessed this hypothesis using the linear model given above with only N2 and MA24 included.
Identification of significant differentially expressed genes was determined using the Linear Model for Microarray Data (Limma) package in Bioconductor [19].
We used the linear model "~0 + time-point + AML1-ETO".
The data was analyzed using the linear model described in the Materials and Methods.
That way b is a function though, and we can't use the linear model.
First, we repeated analyses using the linear model (RR = 1 + bx).
We first analyzed the relationship between gene expression variation and number of cis-elements [ 26] using the linear model.
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