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For both datasets, we find that augmenting our training set with simulated evolution yields better sensitivity and specificity than training only on real known protein sequence examples even with either type of entropy weighting.

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In both datasets, we found significant brain size effects in the right amygdala and the bilateral caudate nucleus and significant gender effects in the bilateral putamen.

We utilized an ad hoc method for doing initial categorization in both cases, but after extensive manual examination of the mutations classified as activating in both datasets, we found that the SWISS-PROT mutations are more likely to provide interpretable results.

Bonina agrees: "It's not the same for you and me to sit at a computer and try to use datasets we find interesting compared to big companies like Google, Facebook or banks which have computing power to really process the data.

For each of our 1500 bootstrapped datasets, we find the 'optimal' set of parameters using SRES.

In these datasets, we found 79 genera occurring in both human and mouse gut microbiotas.

For all datasets we found negative linear relationships between the coefficient of variation and the mean soil moisture, indicating lower spatial variability at higher mean soil moisture.

With respect to the ALL datasets, we found that empirical Bayes statistics was the most biologically (functionally) supported method for the ALL1, ALL3 and ALL4 datasets.

In all datasets we found evidence for a large number of bacteria belonging to diverse taxa.

Finally, when comparing our rat dataset (10 K genes) and the Novartis GNF dataset human (10 K genes) datasets, we found 368 common genes between the datasets.

Analyzing 17 real datasets, we found that the LR test substantially outperformed the score test (Table 3).

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