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Huang et al. [ 29] have used sequence and structural information to predict DNA-binding residues in transcription factors, while Jongkon et al. [ 30] have predicted the binding preference of various strains of avian influenza A to cognate human receptors.
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We constructed the binding preference of each TF with a simple heuristic which assesses the binding preference for a TF from a set of known binding sites.
The final binding preference of each TF is made by taking a vote among these six binding preferences, and again in case of a tie random binding preference is assigned.
The binding preference of these receptors greatly increases the complexity of ABA signaling pathway.
Substrate accessibility should be a key determinant for binding preference of LPMOs.
With the assumption that the binding preference of a TF is the same to all its binding sites, we estimated the binding preference of each TF with the following heuristic.
The positive data sets are constructed from 226 known binding sites in our test data set by splitting the known binding sites into single- and double-strand binding sets according to the binding preference of each TF.
We also included the binding preference of RSC for bare DNA, as observed with AFM.
The binding preference of a known transcription factor can be described by the sequences to which it binds.
Based on a directed evolution approach, here we provide the first quantitative characterization of the binding preference of the DYNLL binding site.
This binding preference of EGF4KDEL for malignant cells was also observed in protein synthesis inhibition assays.
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