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Even in small samples and low computational cost, its performance is still very robust.
The measurements employ scanning calorimetry on both emulsified and non-emulsified samples, and low- and high-angle X-ray diffraction.
Barcode sequences were used to assign raw data by samples and low quality sequences were trimmed and excluded to obtain valid tags.
However, no significant differences were observed (P > 0.05) between high fat and medium fat samples, and low fat and medium fat samples.
There was a general consensus among our intensivists that three negative lower respiratory samples and low clinical pretest probability were needed to exclude MERS-CoV infection.
PLAP levels were undetectable in 4 of 5 cord blood samples and low in the remaining one (Table 3).
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Cumulative survival time of high-risk samples and low-risk samples was calculated by the Kaplan-Meier method [17] and analyzed by the log-rank test [18].
Criteria (a) through (e) were used to exclude pseudogenes, contaminated DNA samples, and low-quality sequences.
However, we observed low-levels of procaspase-9 in GBM patient samples and low-levels of procaspase-9 and ApApaf-1n the GBM cell lines, when compared with the HeLa control.
The main sources of error were found in human transcription, mix-up of samples and low-quality sequencing raw data [8,9] that could be avoided by an automated and customized software-controlled process.
However, CE-based analysis has its limitations, for example, the inability to analyze multiple genetic polymorphisms in a single reaction using a single workflow, low-resolution genotyping of current markers, loss of useful genomic information from degraded DNA samples, and low-resolution mtDNA and mixture analysis.
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