Sentence examples for using the prediction analysis from inspiring English sources

We next tried to design a predictor with a minimum number of CpG sites using the Prediction Analysis of Microarrays tool (PAM) [28].

We tried to assign 11 genetically heterogeneous cases of type AB into types A and B using the prediction analysis.

Samples were labeled as normal, LMP, or stage III for class prediction using the Prediction Analysis of Microarray (PAM) classification algorithm, with separate training and test sample sets as recommended by Simon et al. [ 21].

Finally, we used the prediction analysis for microarray (PAM) method to identify gene signatures of cigarette smoking and cancer, and uncovered a 15-gene signature that distinguished between SNC and SC with an accuracy of 83%.

In addition, we performed a sensitivity analysis using the prediction horizon for which each model was developed in case this differed from 5, 7.5, or 10 years.

In silico analysis using the prediction programs Mutation Taster (http://www.mutationtaster.org) and PolyPhen-2 (http://genetics.bwh.harvard.edu/pph2/) classified variant I as a benign polymorphism (rs1131188481).

Using the prediction method of log linear regression analysis, the probabilities of any kind of orthopedic fracture by gender and by age strata could be compared (P < 0.01, age strata tested by the linear trend test).

Because the sample size included in the current study is relatively small, we estimated the effect of sample size on the accuracy of the prediction analysis using the data from a previously published study of eye color (Liu et al. 2009), in which a larger sample was available (N = 6,168).

Eleven cases of type AB were used as a test set in the prediction analysis.

Putative leader sequences (indicative of secreted proteins) and N-glycosylation sites based upon the NX(S/T) motif were predicted by SignalP 3.0 and NetNGlyc 1.0 Server, respectively, using the Center for Biological Sequence analysis Prediction Servers [ 56].

The 30-gene set used to differentiate subtypes was determined using prediction analysis of microarrays (PAM) (Tibshirani et al, 2002), which was optimised by minimising the cross-validation training error (see Supplementary Table 2).