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Since the predicted CHF values did not match the experimental values (due to the heater size effect), Kandlikar's CHF predictions were modified by multiplying by a constant factor to fit the experimental data for the bare oxidized silicon and bare Teflon-coated surfaces, as follows: q ″ CHF = F × i fv ρ v 0.5 1 + cos θ R 16 2 π + π 4 1 + cos θ R cos φ 0.5 σ g ρ f − ρ v 0.25 (1).
Altogether 76 predictions were modified.
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Key thermal environmental data predictions and monitored values are compared, and if significant differences are identified, thermal environment predictions are modified.
Authors' response: We use the information from the TOPDB database to modify the result of SignalP, and not from the UniProt, moreover the order is the opposite: first we generate the SignalP prediction and this prediction is modified, if the TOPDB database contain contradictory data.
This prediction was modified if a homologous protein in the TOPDB database had an annotated signal peptide that was not predicted by SignalP, or vice versa, if the corresponding TOPDB entry had not contained a signal peptide, but it was predicted by SignalP.
LibSVM open-source Java codes were modified and embedded in the system source codes for prediction.
Models were modified to take into account protein binding to the polymer but the modified predictions were still larger than the measured values.
Pedigrees were modified accordingly.
The original splicing predictions have been modified for some genes, taking into account alternative predictions and the structure of closest homologues (see Results, Table 1 and Additional file 1).
Then the short-term forward prediction method was modified to successfully extend the prediction term.
A yield zone load interaction life prediction model was modified to include temperature dependent properties.
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