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The quality of such predictions is therefore highly dependent on the amount of experimental training data available [2].
A brief review of these theories, their key principles and predictions is therefore necessary.
Improving the accuracy of secondary structure predictions is therefore important for future genomic studies.
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Biomass predictions were therefore influenced more by the 2D remote sensing data than the lidar inputs.
Accurate gene predictions are therefore achievable when reliable sets of homologous proteins are not available.
Our model predictions are therefore limited to the 40% of the population with the MM genotype.
Previous predictions were therefore limited to three bacterial phyla: Proteobacteria, Firmicutes and Actinobacteria.
The model predictions are therefore determined independently from the lightning observations.
These predictions are therefore independent of the ones in the original species.
These predictions are therefore added to, and in some cases replaced by predictions made from genome sequence.
These predictions are, therefore, consistent with observations that many kimberlites are strongly altered volcaniclastic deposits that had high initial porosities.
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