Sentence examples for binding sites are generated from inspiring English sources

In the next step (see Figure 1), sequence based predictions for transcription factor binding sites are generated by PoSSuM [ 10], in particular based on the JASPAR position specific scoring matrix database [ 21].

A dataset of ligand-dependent binding sites was generated using the SiteHopper create tool [13] where default parameters create a binding site patch within 4 Å of a specified bound ligand.

A genome-wide map of predicted STAT1 binding sites was generated as follows.

After formation of the dityrosine bond a complete set of well-formed zinc binding sites is generated.

All the designed mutant nucleotide sequences were re-analysed in Match 1.0 Public to check for loss of the specific transcription factor binding site and that no new binding sites were generated.

A binding p-value was then determined for each genomic position by Wilcoxon rank sum test and binding sites were generated from those more significant than specified thresholds with a maximum gap of 500 and minimum run of 350.

Two different types of sets of example binding sites were generated for each cutoff score from 2 to 7. They correspond to sequences drawn from a step-function distribution or a Boltzmann distribution, in each case using a maximum energy cutoff for selected sites.

Mutations in the miR-200c binding sites were generated by PCR directed mutagenesis.

In order to decrease endogenous miR-181a-5p miR-181a-5p miR-181a-5puct with four repeats containing miR-181 binding sites was generated.

For this purpose, either single mutations or the possible combinations of the potential binding sites were generated.

The plasmid pCAG-125b-6 pCAG-125b-6 pCAG-125b-6 copies of binding sites was generated using the isocaudamer of SpeI/ NheI.