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Although microarray data based on analysis of end-point PCR amplicons is not quantitative, results showed a significant signal reduction when targeting killed cells and consistently agreed with qPCR results.
These genes were selected from the microarray data based on i) their minimal variability between the control and infection group ii) their absolute expression level covering the whole array signal range.
The microarray data based on signals from polyadenylated chloroplast transcripts also indicated that PSII genes like psbE, psbH, psbY and psbX were down-regulated as a response to the HL treatment during some or all of the acclimation phases.
There is not a strong consensus among the three gene sets we used [23], [24], [26], with about 13% (69/513) overlap, There are 67 genes in common between the two microarray experiments and two between the ChIP [26] and the McElwee et al. [23] microarray data, based on our filtering criteria.
We used different methods to analysis the microarray data based on different hypotheses.
256 genes were selected from the microarray data based on association with smoking or coronary artery disease (CAD).
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Of these, elements that are key to functional genomics studies are the protein protein interaction data and meta-expression data based on microarray data analyses.
The expression data based on microarray experiments belong to three datasets: DeGregorio2001, Arbeitman2002, and Spellman2002.
We compared genes that are found in both the microarray data and the SAGE data based on their fold increase.
Data based on genomics, microarray hybridization results, and validated by polymerase chain reaction and slot blot DNA hybridizations.
It has also been observed in other studies that the quantitative PCR values are, in general, much higher than microarray data, whether based on oligonucleotide or cDNA microarray platform [ 38, 39].
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