Sentence examples for work with expressions from inspiring English sources

For simplicity, Kaneko [22] and Solomon et al. [23] work with expressions valid for small protraction angles (θ<∼14°), an approximation that appears to be valid for rat whisking behavior [4], [31].

compares and contrasts MCF7 lines from different laboratories; examines the same subculture taken at different time intervals; and most importantly, compares the CGH analytical work with expression array results.

It was designed to work with expression data from microarrays containing large number of features (Np > 10), allowing one to analyse the distribution of all features on a microarray mapped to a three dimensional space composed of average difference of feature expression (logarithm of fold change), total variance and average expression level.

Whereas Jones et al (2000) have already demonstrated extensive variation among different MCF7 cell stocks, this is the first report that: compares and contrasts MCF7 lines from different laboratories; examines the same subculture taken at different time intervals; and most importantly, compares the CGH analytical work with expression array results.

It also works with expressions of multiple words ("beside the point").

Obviously the work resonates with expressions of the African diaspora, but the appeal of Basquiat in Brazil seems to go even deeper.

Thus, when working with expression profiles, we would like the model to allow lower similarity levels between genes that are not necessarily regulated on the expression level, while penalizing heavily for low similarity between transcriptionally regulated genes.

While it is not always possible to express in closed form, one can always work with the expression numerically.

We tried to work with that expression to make the space bigger and smaller, to deform it and to change its surface over and over while not exaggerating and overwriting the original effect of the room," Bauer tells us.

In other words, we chose to work with 28 expression patterns for which a random sequence has low fitness.

This builds on our previous work with gene expression-based signatures, which were derived using the same approach, and which showed that drug response signatures predict whether a tumor or cell line will be sensitive or resistant to a drug [ 49, 51, 52].