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Although local effects of gp130 dependent down-regulation have been described [7], we aimed to study the consequences of gp130-deficiency in our model system in a broader context using a microarray time-course experiment.
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At the product level, the frequency of subfunctionalization is no higher than would be expected by chance, a finding that was corroborated using yeast microarray time-course data.
We corroborated this finding using yeast microarray time-course data by showing that even the oldest paralogs exhibit similar frequencies of temporal subfunctionalization to what would be expected by chance.
The mRNA expression apparent in the captured in situ images was verified by independently derived microarray time-course analysis using Affymetrix GeneChip technology (more details can be found at http://insitu.fruitfly.org, and in Tomancak et al., 2002).
As an application example, we analyzed microarray time-course gene expression data from rat skeletal muscle [ 42, 43].
In this paper, we introduce a new multivariate data analyzing technique, the correspondence analysis, to analyze the high dimensional microarray time-course data in case control design.
Extracting binary signals from microarray time-course data.
Tai et al. ranked DE genes using data from replicated microarray time course experiments, where there are multiple biological conditions [ 15].
Finally, fluorescence images were captured using a microarray scanner (Axon).
Using a comparative time course study, we investigated the dynamics of transcriptome profiling during this critical stage applying DNA microarray assays and regulatory analysis.
Microarray time course experiments using inhibitor treated cells followed by inhibitor removal were conducted for U0126 and LY294002 similar what was done for the cetuximab and gefitinib experiments.
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