Sentence examples for between two expression vectors from inspiring English sources

For instance, why is the differential co-expression value best defined by an Euclidean distance between two expression vectors (normalized by a squared root of the number of vector dimensions, equation 1).

Their mutual Pearson correlation, r = (x, y ) is then defined as: (1) where, corresponding to the differences from the mean expression of each gene in the X and Y sample respectively and θ is the angle between two expression vectors.

If the pairwise Pearson's correlation coefficient between two expression vectors (profiles) is denoted by ρ, the Pearson's pairwise distance was calculated as All the unique pairwise distances within a set of profiles are computed and the distribution of pairwise distances is summarized by its mean or its median.

The comparison between the two expression vectors (pBluescriptSK- cphE(pBluescriptSK- cphE::cPstIPstI)) showed much lander pBBR1MCS-4 cphEs with PstI1MCshowedphE(PstI) after overnight incubation of CGP-overlay plates at 37°C (Figure 2). Figure 2 Degradation halo formuchon around CGPase producing E. colargerains on CGP-overlay agar plates.

Co-expression values for individual pairs of genes were defined as Pearson's correlation coefficient between the two expression vectors across normalised hybridisation experiments [ 1, 2, 5- 7, 12- 16, 16].

Two expression vectors, pET-SUMO (Invitrogen) and pET-32a (Novagen, North Ryde, Australia), were used in this study.

More specifically the similarity between two expression profiles is equivalently defined as the dot product of the corresponding high-dimensional vector representations.

In order to calculate r MMC between two given gene expression vectors, we must estimate these parameters from the data.

To compare the expression efficiency of the sgRNA in Dictyostelium under the control of a different promoter, we constructed two sgRNA expression vectors derived from the U6 promoter or isoleucine tRNA.

Two different expression vectors with either a Flag or a 5X-Myc tag were used.

We computed two distances between relative expression vectors: the Euclidean distance, d E = ∑ j = 1 n (x R h j − x R r j ) 2 and correlation-based distance, d cor = 1- r(x R h, x R r), where x R h, x R r are relative expression levels for any gene in human and rat, respectively and r stands for the Pearson correlation coefficient.