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According to the expression measures from microarray experiments, extreme sequence lengths (either primary transcript length, total/average intron length per gene or CDS length) most likely scale as logarithmic functions of expression levels which could be expressed as L max = L0- k * log2 N, where L0 > 0 denotes the maximum sequence length when N = 1 and k > 0 is the scaling factor.
Employing pattern classification techniques, we have designed expression classifiers for the four universal emotions of happiness, sadness, anger and fear by training on RVD functions of expression changes.
The pictures based on microarray expression data seem to be different, as extremes of structural characteristics better scale as logrithmic functions of expression levels.
Furthermore, the relationships between expression level and structural parameters seem to be non-linear, with the extremes of structural parameters possibly scale as power-laws or logrithmic functions of expression levels.
Furthermore, the extreme values of sequence lengths likely scale as power-laws or logrithmic functions of expression levels which could be better reconciled with the time-cost hypothesis, rather than to be interpreted by the energy-cost hypothesis.
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However, our analysis of variance (standard deviation) as a function of expression (total tags) indicates that this level of detection is probably not within the range of reliable quantification.
While overexpressing Hha to complement biofilm formation, we noticed it decreased cell growth in both media as a function of expression level (Figure 2); hence, overexpression of Hha is toxic.
That d N is a decreasing function of expression level is the main prediction of the model.
This pattern indicates that translational selection favors short proteins as a function of expression.
The Euclidean distance should be used with caution as an estimator of gene expression conservation because it varies as a function of expression specificity.
Application of this approximation to each bit allows prediction of specific activity as a function of expression level (the rising curve in fig. 2 a ).
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