Sentence examples for microarray analysis highlights from inspiring English sources

This microarray analysis highlights clear differences in the expression of apoptotic genes in infected cells compared to uninfected cells, and interestingly, STS does not affect this pattern of apoptotic gene expression in infected cells.

The observation that only a limited number of contigs show lasting responses to prolonged cold, at least within the detection limits of microarray analysis, highlights the importance of VRN1 in the vernalization response of temperate cereals.

Microarray analysis highlighted activation of pathways involved in apoptosis induction, autophagy, RNA/protein metabolism, starvation responses, and solute transport.

Our microarray analysis highlighted a set of stress responsive genes whose transcription was early affected by As III).

Candidate genes identified through microarray analysis highlight those that are highly differentially or chronically expressed, whereas those identified through network analysis instead feature genes that are highly connected.

Our microarray analysis highlighted marked changes in several molecular pathways in CM-S compared to CM-R mice, particularly at early stages of infection.

A significant perturbation in the angiogenesis and inflammation gene pathways was also observed by microarray analysis, highlighting that gene expression analysis is a crucial issue for the study of common diseases.

With respect to the underlying mechanism of BiP-mediated increases in water deficit tolerance that provided the foundation for pursuing these studies, the results of the microarray analysis highlighted relevant insights.

Unsupervised clustering performed by using processed data from miRNA microarray analysis highlighted differential expression profiles of 48 miRNAs, interestingly clustering the samples into 2 groups, OA versus normal chondrocyte micropellets.

Our microarray analysis highlighted significantly greater evolutionary diversification of RNA localization in the dendritic transcriptomes (81% gene identity difference among the top 5% highly expressed genes) compared to the transcriptomes of 11 different central nervous system (CNS) and non-CNS tissues (average of 44% gene identity difference among the top 5% highly expressed genes).

Microarray analysis also highlighted the differential expression of many stromal extracellular matrix proteins that may act as paracrine signals between the stroma and the epithelium, but which have not been pursued here.