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Table 1 lists the results for the six single-end datasets created from the paired ends, along with the true mean fragment lengths.
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There are different methods to automatically design these thresholds from the historical dataset created from the metrics and indicators provided by the OSS of both LTE network and its uRAT (e.g., 3G) during a period of time.
We used these programs to sort four datasets created from BLASTP searches.
Third, we applied these adjustment models to datasets created from US Food and Drug Administration FDAA) reviews of antidepressant trials and from their matching publications.
SVM-RFE is used to find discriminate relationships within clinical datasets and within gene expression datasets created from micro-arrays of tumor versus normal tissues.
Here we benchmark a state of the art disorder predictor, DISpro, on a large protein disorder dataset created from Protein Data Bank and systematically evaluate the relationship of sensitivity and specificity.
The system is evaluated with a dataset created from 20 MIDI files of Bach quartets where either two or three of the voices are created by inserting instrument notes taken from the RWC music instruments dataset.
(i) Realistic dataset with variable length (RealVar dataset): This dataset consists of total 14725 BCEs (i.e., 11981 IgG-specific, 2341 IgE-specific, 403 IgA-specific BCEs) and 22835 non-BCEs of variable lengths (Table 4) (ii) Balanced dataset with variable length (BalanceVar dataset): This dataset was created from the above mentioned RealVar dataset.
The proposed method is tested against a dataset created from public DNA sequences provided by InSNP.
Hecker et al. [ 13] developed a state of the art protein disorder predictor and tested it on a large protein disorder dataset created from Protein Data Bank.
We evaluated the performance of our three; i) rm-useless, ii) PCA based, and iii) CfsSubsetEval based models using validation dataset created from MACCS fingerprints (see detail in material and method section).
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