Sentence examples for both gene expression datasets from inspiring English sources

As the quality and the extent of both gene expression datasets and, more importantly, the human PPI network are expected to vastly improve, we believe that this approach will be widely adopted.

While none of the interaction datasets change significantly with this process excluded, both gene expression datasets show substantial decay in their precision-recall characteristics, suggesting they are generally less reliable at predicting functional relationships over a broad range of processes.

The FTP site includes RData files for both gene expression datasets as well as an HTML transcript of the analyses performed, which we highly encourage readers to examine as all analysis details are included in addition to a number of summary plots exploring the dataset.

We collected two latest gene expression datasets (both EST and microarray data) from public databases and analyzed the gene expression profiles in 18 human tissues that have been well-documented by both two data types.

By performing statistical integration of both the microbiota and host gene expression datasets, (mixOmics R package), we tracked changes in jejunal gene expression which follow the changes in microbial populations as determined on the same location in the gut.

We implemented our procedure for estimating p A in several gene expression datasets, both proprietary and public, in which expression data was generated from samples composed of two tissue/cell types.

In an analysis of two gene expression datasets, both representing the types of class-comparisons that are typical in microarray studies, we established that the use of domain-specific knowledge in the form of prior network seeds can improve the ability of Bayesian Network analyses to learn known interactions between genes.

Thus, the highly coordinated genome-wide transcriptional response which was observed in gene expression datasets of both malignant and non-malignant tissue impacts on the pattern and magnitude of the observed gene expression changes.

Finally, we tested translatability and tissue-specificity of the signatures by identifying the coverage of genes in several baseline gene expression datasets in both mouse and human (Supplemental Table S3 in Additional file 5).

However, reanalysis of multiple gene expression datasets using both microarrays and RNA-seq shows that median expression levels of X-linked genes when assayed in whole testes are in fact approximately 1.5-fold lower than those of autosomal genes (Meiklejohn et al. 2011).

Both features are critically important for increasing the power of identifying co-expressed genes in large scale gene expression datasets.