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For the male classification model, the specificity was 90.3% and the bootstrapped sensitivity was 51.0%.
For the female classification model, the specificity was 90.0% and the sensitivity was 37.1%.
Therefore, it is neccessary to investigate multivariate and feature-selective methods to model the specificity and to extract rules from the model.
The only significant difference was for NTproBNP ≤300ng/L; when adding prevalence differences into the model the specificity was significantly higher at 0.93 (95% confidence interval 0.84 to 0.97, P<0.01).
Furthermore, based on the flow cytometry inhibition assay using IGROV1 cells as an investigative model, the specificity of monoclonal antibodies to P1 as shown by the full saturation of anti-P1 antibodies by inhibition with 0.06 μmol glycan on sepharose beads indicates that IGROV1 expresses P1 on the cell surface.
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Several machine learning algorithms have recently been applied to modeling the specificity of HIV-1 protease.
For model specificity, the specificity of FSP + CVHI + inflammatory cytokine model alone exceeded 90%.
In this organism, an elegant 'self-reinforcing loop' model explains the specificity of heterochromatin formation based on the role of the RNAi machinery (reviewed in [7] [9]).
As a model for the specificity of a transcription factor we use the quantitative binding data obtained for the Mnt protein of phage P22 [3].
The specificity of the model exceeded the specificity of any D-dimer method in tested in both the validation group as well as the entire cohort, tested by latex agglutination, ELISA, and immunoturbimetric methods which showed sensitivity/specificity of 63.2%/60.5 %, 97.4/21.1%, 97.4%/21.1 %, 97.4ctively (Table 2).
The docked model explains the specificity of inhibition.
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Justyna Jupowicz-Kozak
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