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Previous methods that performed similar analysis showed that such a measure can be used to infer DDIs [11], [16], [24].
Again, the other methods that performed relatively well were percent present and PM/MM t-test.
In a recent critical assessment of methods for constructing gene networks [ 18] WGCNA was found to be one of the methods that performed the best for constructing global co-expression networks.
One of the methods that performed best in this task was a simple approach, strictly data-driven, that encodes significant effects of stimuli and inhibitors on measured proteins in a cause effect network (Eduati et al., 2010).
Methods that performed well to de-identify text include machine learning approaches based on CRF, Decision Trees, Maximum Entropy models, or SVM, combined with dictionaries and sometimes regular expressions.
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However, it is only adequate to train methods that perform NER of pharmacological substances.
However, those methods that perform better than the proposed method use more reliable proprietary software for face detection.
Presently, methods that perform array processing while aiming to preserve interaural cues can be divided into two general categories.
Attractive methods that perform simultaneous reconstruction of missing structures and textures in images have also been proposed [1, 2].
This sets it apart from other fast SR methods that perform nonuniform interpolation and restoration as independent processing steps.
So far the focus has been mostly on creating and testing methods that perform one of the steps of the text-mining process (see for example [1 8]).
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