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Every presently known plasma proteomic method still only samples a relatively small fraction of the proteome that mostly consists of the relatively highly expressed proteins [ 81, 82].
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However, despite the multitude of inference methods available, these methods are still only capable of inferring 'moderately large dynamic networks' (Kim et al., 2013).
However, this method still assumes only additive errors and requires a lot of prior information about the parameters.
The method's efficiency is still only a few percent--enough to produce substantial amounts of factor IX in mice, but not enough to treat other diseases and larger animals such as humans.
However, our multi-method model of mothering still only explains about two percent of the variation in infants' cognitive development.
Although both sensitivity and precision decreased slightly, reasonable performance was maintained with a cutoff of six (Table S3), suggesting that the method still works for situations where only one tenth of input genes are disease-associated.
Moreover, as reported here, applying multiple technologies and methods to a personal genome still only reveals the tens of thousands of reference-inconsistent loci that could indicate the presence of structural variation.
When applied to pedigree data only, the proposed method still may have improved power over traditional TDT-based methods, as shown by analyses using the software FBAT.
But research into the method still continues.
More variability is seen in the ranking of the top 50 peaks, though the methods still differ by only 10% when the outliers (PeakSeq and HPeak) are excluded.
Many studios using her method still operate.
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