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However, neither of the two above methods is capable of appropriately dealing with incomplete baseline sample.
Neither of these prior methods is capable of estimating isoform expression levels, and thus we compared only gene expression estimates.
The ability of ABVS to image large benign and malignant lesions automatically and UE to determine lesions stiffness effectively led to the assumption that the combination of these two methods is capable of detecting clinically occult benignancy and malignancy.
Since the algorithms for enzyme function annotation employed by EFICAz and KEGG are different, and their sources only partially overlap, it is expected to find some sequences for which both methods make functional assignments (which may agree or disagree), and other sequences for which only one of the methods is capable of making an EC number assignment.
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Both methods were capable of providing notch at locations of interferences signals.
The sparsity-driven methods are capable of providing good performance under strong noise.
Further, unsupervised learning probabilistic methods are capable of handling the uncertainty and incompleteness of sensor data.
All the methods were capable of determining the location of the sound source with varying accuracy.
Further, they proved that in both cases only bootstrap methods were capable of statistical inference.
All methods were capable of calibrating the model when given enough computation time.
Both methods are capable of parametrically identifying nonlinearities from measured frequency response functions.
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