Sentence examples for mapped gene expressions from inspiring English sources

Piro et al. [ 12] proves that spatially mapped gene expressions are suitable for candidate gene prioritization.

Ebert and Regev have mapped gene expression in blood stem cells as they mature into different types of blood cells.

A classic study mapped gene expression activity in 5 spatial regions across 3 developmental stages [1], yielding 15 spatiotemporal snapshots.

For this, we mapped gene expression data from microarrays onto the corresponding enzymes and their metabolic reaction network.

The aim of this article is to provide a proof-of-concept for the suitability of spatially mapped gene expression for candidate gene prioritization.

We mapped gene expression data onto optimally arranged grid representations of pathways of the metabolic network and applied Haar wavelet transforms onto defined pathways of the network to combine gene expression values from neighboring enzymes.

A recent study [ 70] describes the prioritization of XLMR candidates based on spatially mapped gene expression, and focuses on the 718 genes on the X chromosome recently resequenced by Tarpey et al. [ 51].

In order to construct composite networks representing different growth conditions, we have mapped gene expression data onto a parent network of combined protein-protein interactions and gene regulatory interactions (Methods).

We also mapped gene expression patterns in chdA, chdB and chdC nulls that had been induced to synchronously differentiate by cAMP pulsing, to a time point akin to ∼8 hours of development, when cells are chemotactically competent (Fig. 4C).

This normalization mapped gene expression value is generated from different protocols into a uniform framework so the impact of the different protocols on the data integration can be reduced.

We compared the regulation of signaling pathways in cancer with normal cells and mapped gene expression data of tumors and their corresponding non-malignant ("normal") samples onto a comprehensive protein-protein-interaction network.