Sentence examples for predictions we constructed from inspiring English sources

To verify the relevance of in-silico predictions, we constructed a PGAA + Phe24βCys mutant and determined its enantioselectivity in biocatalytic reactions.

To experimentally test our model's predictions, we constructed a tetraploid series of deletion mutants for a set of eight genes that control the G2/M transition.

In the course of making these predictions, we constructed multiple functional linkage networks [FLNs where an edge between two genes indicates some level of shared function (Lee et al. 2004)], capturing different categories of biological relationships.

To confirm this prediction, we constructed luciferase reporter vectors and performed the luciferase reporter assay.

Inspired by recent advances in PPI prediction, we constructed a PPI map of this important fungus.

To test this prediction, we constructed isogenic strains carrying either the siz1Δ ::HIS3MX6 or the pol30RR mutations and measured the spontaneous CO levels.

To encapsulate these complex patterns of residue conservation and position-specific propensities for computational prediction, we constructed SVM prediction models using features extracted using the Bayes Feature Extraction (BFE) approach recently introduced by Shao et al.[ 19].

In order to further corroborate this prediction we constructed 3D models of the four geminiviral CPs (Fig. 4A) and tested the stereochemical quality, along with the X-ray structure of the STNV CP (see Methods for details).

To determine which features were relevant for protein stability prediction, we constructed SVM classifiers using each of the twenty sequence features listed in Table 2 for input encoding (w = 11).

To test this prediction, we constructed for Danio rerio a genetic map (RADmap) by using RAD-seq and Stacks to re-genotype a previously published doubled haploid mapping panel (HSmap, http://zfin.org/cgi-bin/webdriver?MIval=aa-crossview.apg&OID=ZDB-REFCROSS-000320-1) that consists of 42 progeny (Kelly et al. 2000; Woods et al. 2005).

To examine this prediction, we constructed alignments of the wild and cultivated consensus sequences containing only the good quality positions and the SNPs predicted by our algorithms, and surveyed each alignment for signatures of positive selection using the McDonald-Kreitman test [ 26].