Exact(2)
It may be seen that, in the cases of PSICOV, OMES and DCA, the maximum improvements in contact prediction upon combining amino acid and codon data are when these distances are about 5.5, 7 and 5.5 Å, respectively, and that, in the cases of DCA and OMES, the improvement decreases dramatically when this distance is >∼10 Å.
These data, therefore, show again that the improvement in contact prediction upon combining amino acid and codon data is greatest when the distance used for contact definition does not lead to many pairs being defined in contact when in fact they are not in direct physical contact.
Similar(58)
4. Predict outcomes of the summit using the information obtained and shared in class; evaluate predictions upon the conclusion of the summit.
"It appears ― and again, we're looking at it closely, I have a brief when I get back ― it appears they took the worst scenarios and they built predictions upon that," he said of the report's authors.
The pTARGET algorithm bases predictions upon Pfam domains that are uniquely located in specific subcellular compartments.
Many of these programs base predictions upon existing quantitative peptide binding affinities for specific MHC molecules [26], [27], [28], [29].
We first compiled unique predictions for only three methods (Ucon, NORSnet and DISOPRED2) and then compared this to the unique predictions upon including MD.
Of the available prediction algorithms such as miRBase, PicTar, miRanda, PITA and TargetScan, all of which use site conservation as a prediction criterion, the latter was shown to result in the most accurate predictions upon target validation [27], [28].
DOI: http://dx.doi.org/10.7554/eLife.03568.009 10.7554/eLiFigure68.010 Figure 4 figure supplement 1. Variation of predictions upon variation of the memory time scale of the LBI λ i.
By incorporating gene regulation into our model we are able to perform steady-state analyses to make predictions upon the likely efficacy of potential systems biology approaches.
Model checking could facilitate such repetitive designing processes by performing automatic checking of biologically plausible models and suggesting new testable predictions upon every model-based simulation failure [ 11, 20, 61- 65].
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