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Hence, given a genome-scale metabolic network model, many samples of genome-scale metabolic flux data need to be generated under the condition of interest, by introducing random errors to each flux value.
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Each read class contained reads with a fixed number of introduced random errors relative to the consensus genome sequence.
To simulate genotyping errors, we also introduce random errors to the resulting genotype sequence.
We introduced random errors as above, using empirical error distributions that take into account the increased number of generations.
Simple programmes were written to introduce random errors and omissions into new versions of the definitive 10-year Butajira dataset.
For most assemblies, read errors are simulated by introducing random mutations at a rate of 0.6% per base, random indels at 0.2% per base, and errors in the homopolymeric run count producing an additional 0.2% errors per base for a total 1% error rate.
This method has been shown to be valid [38], [39]; any imprecision in the recall would likely introduce random error and attenuate the results.
Poorer data recording in Senegal introduced random error that reduced the precision of the CBCA instrument.
Inaccuracies in 24-hour urine collection may have introduced random error and biased results towards the null.
We further extended this model by introducing random and systematic variation in enzyme activity.
The study was later extended, e.g., by introducing random mutation of interaction strength in various replicator networks [ 7] or by introducing random growth in replicator networks [ 8, 9].
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