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While, template selection is an effective method to reduce the number of fingerprint templates in database.
In this section, the proposed template selection is compared to MDIST [10] template selection.
The rule of thumb for template selection is to favor the proteins whose sequences align better with the targets in the important regions, such as the adenosine-5'-triphosphate (ATP -binding pocket in kinATP -bindingnsmembrane domains in G pocketn-coupled receptors (GPCRs).
What contributes to the template selection is not clear.
In individuals with hippocampal pathology, template selection is critical (Avants et al., 2010).
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.
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In the first part of this work different measures of similarity in template selection were explored and methods for homology modelling, docking and refinement of aminergic GPCR-ligand complexes were developed and evaluated by comparing models of the D3-R/eticlopride complex with the crystal structure.
However, alignment errors and template selection are still the main bottleneck for current template-base modeling methods, especially when proteins under consideration are distantly related.
The main contributions of this article to the fingerprint verification are (1) a template selection method is proposed, and this method is more robust and effective than the MDIST.
First, in the enrollment stage, some fingerprint images of the same finger are enrolled, and a template selection method is used to choose some fingerprints which are the best represent of this finger as the templates.
Our proposed template selection method is better than MDIST.
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