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Moreover, the use of microarray expression profiling has aided us in capturing neuroadaptations involving complex changes in gene expression that may underlie the development of drug addiction [ 15, 16].
One of these, his most influential, outlines his original use of microarray expression profiles as a phenotypic footprint for gene function.
Our results demonstrate how the use of microarray expression profiling can help assign roles to previously uncharacterized genes and elucidate plant pathogenesis-response related mechanisms.
Several methods make use of microarray expression data (Goeman and Mansmann, 2008; Kong et al., 2006), while others use the biomedical literature associated with genes (Raychaudhuri and Altman, 2003; Zheng and Lu, 2007).
The increased use of microarray expression profiling to study both the molecular biology of cancer and the cellular physiology of difficult-to-isolate cell types has led to a growing need for methods that allow the use of limiting quantities of RNA.
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Using a compendium of microarray expression experiments (Methods), we compiled a list of genes upregulated in the presence of different fatty acid sources.
For these reasons, it would appear likely that qRT-PCR will continue to be used extensively for the validation of microarray expression data [ 15].
We describe a novel approach for systems-level interpretation of microarray expression data using a manually constructed "overview" pathway depicting the main cellular signaling channels (Atlas of Signaling).
The database contains almost 250 000 modules that were generated using multiple analysis methods and integration of microarray expression data.
Ten genes were selected for validation of microarray expression levels using Taqman Inventoried Assays and Real Time RT-PCR.
Evaluation of microarray expression data using the BAR eFP-Browser revealed strongest expression of δOAT in senescing rosette leaves, floral organs and mature and imbibed seeds [ 37].
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