51 research outputs found

    VP running time with various input files.

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    <p><sup>a</sup>The network uploading speed used for comparison was 5 Mbps.</p><p>VP running time with various input files.</p

    PAM predictive analysis of the 19-peptide biomarker panel differentiating PE from control samples.

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    <p>PAM prediction was performed with training data from PE (training, n = 21; testing, n = 10) and control (training, n = 21; testing, n = 10) samples evaluated with the biomarker panel. Samples are partitioned by the true class (upper) and predicted class (lower). The classification results from training and test sets are shown as 2 by 2 contingency tables, calculating the percentage of classifications that agreed with clinical diagnosis.</p

    The serum concentrations of sFlt-1 (left) and PIGF (right) as a function of the gestation.

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    <p>For either PE (red) or control (green) data points, a loess curve was fitted to represent the overall trend of biomarker serum abundance as a function of gestation.</p

    Serum peptide biomarkers identified to separate PE and control subjects.

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    <p>FGA:</p>*<p>cluster 1;</p>**<p>cluster 2;</p>***<p>cluster 3;</p>****<p>cluster 4.</p><p>Score and minimal false discovery rate (<i>q</i> value) were computed using SAM algorithm.</p

    Diagnosis of PE from control with serum biomarkers.

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    <p>Left panel: estimated PE scores were computed from the PE serum peptide panel PAM model as a function of the gestational weeks; right panel: the log sFlt-1/PIGF serum concentration ratio was plotted as a function of the gestational weeks. Red indicates known PE cases; green indicates known healthy pregnancy controls. For either PE or control sample category, a loess curve was fitted to represent the overall trend of biomarker scoring as a function of gestational age.</p
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