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One method of measuring the sensitivity of target prediction algorithms is to compare expression patterns between the predicted target list and the transcription factor whose binding site motif was used to derive it.
The Box Plot analysis and significance analysis revealed a trend of overall inverse association between the predicted target genes and either up- or down- regulated microRNAs (Figure 1B).
The overlap between the predicted target genes and the genes detected as present in the mRNA expression analysis was examined further.
Only gene and microRNA pairs that showed a negative correlation coefficient were selected to form a correlation coefficient matrix between the predicted target genes and the microRNAs.
However, given the significant overlap between the predicted target genes obtainable with both vectors and the existence of restraints on their insertion location, transposable element-based approaches are likely to reach the end of their utility in the near future.
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Next, we confirmed the physical interaction between Sox10 and the predicted target binding sites by chromatin immunoprecipitation (ChIP) assay leading to identification of at least 4 novel direct regulatory targets, proteolipid protein (PLP), Sox10, extracellular superoxide dismutase (SOD3), and pleiotrophin (Ptn).
A third step to reduce the number of false positive interactions is to integrate prior knowledge in form of known functional relationships between the regulator and the predicted target into the inference procedure.
In order to identify microRNA::mRNA associations relevant to ULM pathogenesis, we examined global correlation patterns between the altered microRNA expression and the predicted target genes in ULMs and matched myometria.
We found that there was very little overlap between the predicted targets of each algorithm.
Consistent with the variability in overlapping molecular pathways in our IPA, there was little overlap between the predicted targets among the age-associated oncomirs/ts-mirs (Fig. 4A).
To gain a better understanding of what targets may be regulated by these cancer-related miRNAs, we compared the overlap between the predicted targets for these miRNAs.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com