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In biometric identity verification, a similarity function measures the degree of similarity of an unknown pattern to the claimed identity template.
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Therefore, if only lower sequence identity templates were available, these two scoring functions could aid in selecting the most accurate model.
Furthermore, performing real-time PCR-SSP in a multiplex format allowed the incorporation of internal standardization, measuring in parallel the degree of sequence identity between template and primers, and the amount of template incorporated in the reaction.
In general, the average homology model accuracy is a function of the template-target sequence similarity: The dispersion of the model-target structural overlap increases with the decrease in sequence identity between template and target.
For the HE protein model, we used hemagglutinin-esterase fusion glycoprotein structure of influenza C virus (PDB ID: 1FLC) with 19% identity as template.
However, homology modeling had been employed by other researchers for TbpA in Neisseria meningitides despite low identity between template and target proteins [ 48].
Only minor adjustments were necessary due to the noticeable sequence similarity (22% identity between template and target sequence over the Gfa domain) and the anchoring effect of the conserved cysteines.
This number was obtained after discarding models presenting less than 30% sequence identity (target-template) or G-factors below -1.00 [ 24].
Because identities to templates were < 50% for CRAM-1, MOAG-4, SERF-1, and SERF-2, initial structures were derived by sequential loop refinements in modeller 9.12.
For each precomputed model, PMP displays technical information such as the date of creation and date of verification, the sequence identity of the template and the expected model accuracy based on the evolutionary distance between the target and the template.
The GH5-related cellulase module F1_1, residues 44 to 412, was modeled using 3axx.1.A (87.3% amino acid identity) as the template.
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