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Coefficient of correlation (r) value of 1.0 (both training and validation sets) was achieved for frequency bands ν1, ν2, ν3 and ν4 suggesting perfect model fit.
Consequently a more robust final model (that averaged coefficients from all 10 data sets) was achieved.
Matching between the Norway/Stanford data and the two Swedish data sets was achieved by using Unigene IDs build 181.
The authors agreed theoretical saturation across the data sets was achieved when no new themes emerged during the final interviews.
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The property of the solution sets is achieved.
One immediately observes that the best classification performances for all three data sets were achieved by the SNB approach.
Validation of the derived simple solution set and the proposed procedure to generate further sets is achieved by studying a number of theoretical examples.
The partition into suitable sets is achieved by a finite iterative algorithm, which is made quite efficient because of the interactions of the quadratic programming problems on consecutive data.
Complete data sets were achieved for n = 13 (aggregometry) and n = 10-12 for biochemical measures.
Data reduction and processing of data sets were achieved using the HKL2000 software package and the CCP4 suite of programs.
By comparison of data obtained by simplex MAPH with those by QuadMAPH, we have also demonstrated that multiplexing four probe sets is achieved with no ensuing loss of measurement accuracy, as indicated by the false positive and false negative predictions.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com