Sentence examples for template selection that from inspiring English sources

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We believe that our analysis of the recently solved GPCR structures contributes to a more consistent method for GPCR template selection that opens new ways to fundamentally improve the quality of GPCR homology model building.

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Our previous study on the current template selection method showed that it allowed selection of the trap graft as the best-matching allograft in only 3 of 40 cases.

Since template selection is an important factor that affects quality, therefore, an attempt was made for a suitable template searching using mGenTHREADER [ 14], which is an online tool for searching similar sequences, based on sequence and structure-wise similarity.

If sequence similarity of the entire serpentine domain (the region from the start of TMH1 to the end of TMH7) and helix 8 is used as the sole criteria for homology modelling template selection then a template may be selected that lacks a particular functionally important structural feature.

The large number of template types used suggests that the template selection may be more arbitrary than systematic.

We have performed a rigorous and systematic analysis of the available experimental GPCR structures, identifying common, different and unique sequence and structural motifs that can be used to guide template selection for homology modelling.

In this case, the three templates selected from FVC2004DB4 are all chosen by using the template selection method.

Uludag et al. [10] proposed two typical methods for automatic template selection: the first one, DEND, employs a hierarchical clustering strategy to choose a template set that could be best represents the intra-class variations.

Therefore these results suggest that structural information needs to be included in the decision process of template selection for homology model building.

On the TIMIT task, we provide a detailed account of the factors in the proposed template matching methods that affect the rescoring performance, including local distances, number of GMMs employed for frame labeling, template selection, compression methods and their interactions with the local distances, and the percentage of selected template representatives.

In template selection, the memory overhead was around 6.1 MB when 20% templates were selected to be the representatives.

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