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In this study, we describe a new approach for inferring the efficiency of wobble interactions in the tAI without prior knowledge about the expression levels of the analysed organism.
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In addition, we show that with our approach we are able to infer the efficiency of wobble interactions in non-fungal organisms better than the conventional approach (the tAI that does not optimize these values for each organism separately).
With our approach we infer the efficiency of wobble interactions via optimizing the component of the CUB that is due to adaptation to the tRNA pool (i.e. the correlation between these two measures: CUB and adaptation to the tRNA pool).
The efficiency of the used primers was evaluated by calculating the linear regression of Ct data points obtained with a series of different primer dilutions and inferring the efficiency from the slope of the line.
We first analyse our method in-terms of computation and communication costs which infer the efficiency in privacy and secondly we analyse the method in-terms of recommendation accuracy.
We use these data to understand better the efficiency of glacial erosion and to infer the timing, pattern, and rate of ice loss after the last glaciation.
We infer that efforts to improve the efficiency of transfer should focus on local organisational issues.
That is, the greater ESS/CPU, the greater the computational efficiency for inferring the posterior density of that particular hyperparameter.
PC1D simulated solar characteristics inferred that the efficiency increase of 0.8% for a silicon solar cell can be achieved using silicon nitride SWS over a cell with silicon nitride SLAR and a comparable performance with a cell with silicon nitride and MgF2DLAR.
The efficiency of transduction was inferred with HL-1 cells transduced with pTY2-CMV-GFP and examined for fluorescence by flow cytometry; the percentage of transduced cells was estimated to be between 60% and 70% in all transduction experiments (data not shown).
We determined the efficiency of these measures by inferring the error rate (fraction of bases carrying at least one incorrectly identified SNP) in a pooling setting with different coverage.
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