Sentence examples for inferring expression from inspiring English sources

Because genetic studies (Fry et al, 2009; Cserti-Gazdewich et al, 2011) have provided conflicting conclusions, we measured CD36 expression phenotypically rather than inferring expression from genotypes.

Inferring expression at isoform level provides information for finer-resolution biological studies, and also leads to more accurate estimates of expression at the gene level by allowing rigorous length normalization.

The main difficulty in inferring expression levels for full-length isoforms lies in the fact that current sequencing technologies generate short reads (from few tens to hundreds of bases), many of which cannot be unambiguously assigned to individual isoforms.

Likewise, the statistical analyses used to infer presence or absence of expression from microarray data may result in both false negatives (failure to detect expression) and false positives (incorrectly inferring expression).

Although this global analysis only infers expression and does not provide definitive proof, it suggests that many GPCRs are expressed in human pluripotent stem cells and provides support of our initial hypothesis and directions for future study, including genome-wide sequencing of cellular mRNAs (RNA-seq) and pharmacological testing of each candidate receptor.

In their test, the authors inferred expression dynamics for Esrrb — the probabilities that expression would flip from off-to-on or on-to-off were 0.09 and 0.04 per generation, respectively.

While using detection p-values to infer expression above background for microarrays has been widely adopted25,26, a minimum number of aligned sequence fragments is typically required for RNA-seq (e.g., ≥1027, ≥2028), with the stringency of these cut-offs being dependent on the sequencing depth.

We therefore relied on two mouse monoclonal anti-rhodopsin antibodies: R2-12N and 1D4 to infer expression of Q344ter.

We inferred expression clusters for P. pacificus based on the set of 1 1 orthologs.

We queried these databases using Blastn [ 21] with our retrogene, parental gene and neighboring gene data set to infer expression of a particular gene.

In the results section, we compare the CoGAPS inferred expression signatures in the columns of the A matrix to expression signatures inferred by the coefficients of a linear model.