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In this study, we developed a quantitative method, QChIPat, to identify distinct binding patterns for two biological ChIP-seq samples, and the program is implemented in R, Perl and C++, and run in Linux system.
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We show significantly different (p<0.01) ChIP-Chip binding patterns for factors at the two groups of genes.
We are studying new mathematical and statistical models for quantitatively identifying binding patterns from two groups of ChIP-seq samples in future work.
In order to understand the difference between 3' UTR and 5' UTR binding patterns for seedless sites, we analyzed the weights learned by our model for the two regions.
We performed electrophoresis mobility shift assays (EMSAs) for these two SNPs to determine whether there might be differences in binding patterns for possible transcription factors.
In one of the two cases analysed with both antibodies (case 1; Figure 7), we observed similar binding patterns for TS1 and anti-SSTR2.
Analysis of binding within bidirectional promoters revealed interesting binding patterns for CREB.
Fourthly, it fails to define a binding pattern for each identified differential binding site after comparing two samples.
The results show that these two nsP3 domains share a similar binding pattern for accommodating the ADP-ribose.
We can take the binding pattern for the instantiation of a component, and in the binding process, two reactants are combined to form a complex reactant.
Taken together, these data demonstrate distinct binding patterns of the two rhAbs for epitope(s) within the HA1 domain of H5N1 viruses.
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