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The transcriptional terminators were characterised by comparison between transcripts level using primers upstream of the putative terminator sequence (Terminator) and downstream of the terminator sequence (External).
The premise of a direct correlation between transcripts and proteins is not valid in eucaryotic organisms, due to post-transcriptional and post-translational regulation [ 1, 19].
The RP pseudogene transcription is difficult to identify in microarrays due to potential cross-hybridization between transcripts from the parent genes and pseudogenes.
NVivo allowed us to move easily between transcripts and coding schemes to find patterns in the data.
We have proposed a domain-independent method to automatically create a link between transcripts and Web documents, using a keyword-based characterization of spoken contents.
Here, we show that the fairness of these assumptions varies within libraries: coverage by sequencing reads along and between transcripts exhibits characteristic, protocol-dependent biases.
Correlations between transcripts were calculated as in [50].
Due to the overlap between transcripts, a single probe set might detect more than one gene.
The effects were nearly equally divided between transcripts induced and those repressed (Table S11).
Our RPA analyses cannot distinguish between transcripts generated by non-specific termination or by RNase digestion.
We therefore determined the regulation of different cold-responsive metabolites and investigated potential correspondence between transcripts and metabolites.
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