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Dimou, A. et al. Assessing and Refining Mappings to RDF to Improve Dataset Quality.
The quality of each dataset was assessed using the interfaces depicted in Figs 5 and 6 which provided a quick insight into the dataset quality allowing smart check of important statistics as the number of passed filter reads and duplication rate; % rRNA reads for metatranscriptomic datasets; and % merged reads, their median and average size for metagenomics ones.
In order to improve dataset quality we have solved textual description encoding and numerical value format.
We address a number of critically important aspects of the cognate docking problem that are frequently poorly handled in publications in this area; dataset quality, methods of comparison of the docked pose to the ligand model pose and analysis of the results to determine if and by how much a given method is actually better than another.
Dataset quality was checked for completeness.
Following dataset quality control, phenotype and methylation files were merged.
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Datasets quality checking identified 30 chips to be of insufficient quality for meta-analysis.
Dataset 2, Quality of Elections Data (QED), codes the quality of national-level legislative and presidential elections in 172 countries from 1978 to 2004.
For each dataset, the quality of the alignments obtained with CLUSTALW and MUSCLE, was evaluated with T-COFFEE (CLUSTALW and MUSCLE provided alignments of comparable quality, not shown) [ 45].
This dataset is quality controlled with respect to time and space and is derived from the Global Historical Climate Network (GHCN).
The RM method does not correct data to better fit a model but simply imposes constrains (physical laws) to improve the dataset intrinsic quality.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com