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She and her colleagues, meanwhile, drew on vast, modern datasets to get a clearer picture of what was going on.

Another way is to use the knowledge about the input datasets to get a threshold empirically.

We selected real datasets to get a realistic distribution of protein lengths, composition and protein family sizes (Table 2).

We are presently planning a comprehensive examination of the large number of ENCODE ChIP-Seq datasets to get a better assessment of the issue.

One important challenge in microarray analysis is to take full advantage of these previously accumulated data, e.g., for combining different datasets to get a more comprehensive view in comparative analyses.

We considered four simulation scenarios defined by the parameters in Tables  1 and 2. We used two real datasets to get marker information and estimates of the marker, block and error variance components, which we needed to simulate the true breeding values and phenotypic data, assuming correlated genotypes (Tables  1 and 2).

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As discussed in the above section, we can increase our network depth or use a larger training dataset to get better performance.

The difference is that: MMR uses the validation dataset to get the predictions from these base classifiers and then use these predictions to train a meta-learner algorithm; Adaboost.PL sorts the hypotheses generated from all the iterations from each computing node and then by merging them together a final classifier is generated.

We then applied the phosphorylation hotspot analysis to the predicted phosphorylation site dataset to get a more global view on potential phosphorylation hotspots in the A. thaliana proteome.

For transcription factors with variable binding sites, we need to get many suboptimal binding sites in our training dataset to get accurate estimates of free energy penalties for deviating from the consensus DNA sequence.

These are eudicot species, and therefore, it was apparent that we needed to expand our dataset to get a better understanding of the proteins that cluster with the narbonin and nodulin proteins and the neighboring class IIIb group.

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