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This procedure led to data sets of equivalent size to the reduced-age data sets described above.
However, it may lead to distortions of data and hence greater information loss due to k-anonymization.
This can lead to adulteration of data, which is difficult to detect.
The fact that this technique is so operator dependant can occasionally lead to misinterpretation of data.
Issues with RNA integrity can lead to low data quality and failure of the microarray experiment.
Such pressure can lead to distorted data analysis and interpretation of research results [ 48].
The strikingly different patterns in self-reports and implicit associations in the context of behavioural data inevitably lead to the question of: Which data should we trust?
Analyses of smaller subsets of data lead to the identification of condition-specific modules.
Over sized data centers lead to increased cost of maintaining data centers, whereas undersized datacenters can hurt providers badly owing to possible unfulfilled service agreements with users.
While the complete data cleaning procedure leads to loss of data we believe that data are discarded in an unbiased way with respect to SNP-type and indel-type (see Text S2).
Advances of modern science and engineering lead to unprecedented amount of data for information processing.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com