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The developed automated system for material model parameter identification is validated by comparing the calculated with experimental response of the material.
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Peptide/protein identification was validated by Peptide/ProteinProphet software tools [20], [21].
Theme identification was validated among researchers and discrepancies were resolved through discussions until concordance was achieved.
Protein identification was validated when at least three unique peptides originating from one protein showed significant identification Mascot scores (P <0.05) with False Discovery Rate FDRR < 5%) automatically calculated by Proteome Discoverer.
However, this method of identification was validated previously by examining the hospital records of 155 randomly selected patients with psoriasis, where 73.5% were to found to have a history of vitamin D derivative use (20).
Modification identification was measured with the database search accordingly and peptide identifications were validated with Proteome Discoverer 1.4.
Protein identifications were validated when at least two peptides were found with Mascot ion score greater than 35 for each MS/MS spectrum.
Identifications were validated only when the Mowse (molecular weight search) score was significant.
Peptide and protein identifications were validated using Scaffold v2.2.00 (Proteome Software) and the Peptide Prophet algorithm [ 26].
All reported identifications were validated by manual inspection of the LC-MS/MS data.
Protein identifications were validated with the following filters: protein score >11, peptides score >6 and scored peak intensity (SPI) >60%%.
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