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We explain trade-offs linked to the choice of appropriate evaluation and coverage methods.
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Predictable nodes with observed GO term annotations were subject for evaluation and the coverage was calculated as the percentage of the evaluated nodes out of all nodes in the network.
So, although BETA specifies negative test cases as well as positive ones, the complete process, including oracle generation and evaluation and corresponding coverage metrics, was only carried out for the positive ones.
More informative future studies will need larger sample sizes so as to have more heterozygous SNPs for evaluation, and appropriate coverage of promoter regions, to confirm and expand our findings here regarding relations between SNPs with biallelic loss and expression of mRNA and miRNA.
Differences in the efficacy of various drug regimens are likely to have less of an impact on outcome than ensuring high coverage 29 during an MDA campaign; therefore, large-scale trials should focus on optimal delivery strategies for MDA, as well as the monitoring and evaluation of coverage, cost-effectiveness, and impact in different endemicity settings.
Census officials say the only way to get a handle on the size of both the undercount and the overcount is to use data from a 314,000-household survey known as ACE, or accuracy and coverage evaluation.
Many census officials have contended that the only way to define the size of both the undercount and the overcount is to use data from a third type of count, a 314,000-household survey known as ACE, or accuracy and coverage evaluation.
The SMS technique was able to generate more usable reads in ten of the twelve samples considered in the RNA-Seq quantification and coverage evaluation, producing a mean 78% more reads in these 10 samples.
We evaluate the performance of problem (1) by classification accuracy Accuracy = # Unlabe l ed data c l assified correctly # Un l abe l ed data and problem (2) by two multi-label learning evaluation metrics Coverage and RankingLoss [ 28].
As to other two evaluation measures Coverage and Ranking_Loss, ML-kNN is also superior to RankSVM, BPMLL and kNN.
Our evaluation of coverage and characteristics is based on the Phase II HapMap data, which is the largest catalogue of common SNPs with genotyping information till now.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com