Sentence examples for disordered dataset from inspiring English sources

To this end, the fractional difference in composition between a given protein set (an Archaean proteome), and proteins from the Fully Disordered Dataset (FDD) [ 46, 54] was calculated for each amino acid residues as described in [ 28, 53].

The fractional difference was evaluated as (CX-CFDD /CFDD, where CX-CFDD /CFDDtent of a given amino acid in a given protein set, and CFDD is the corresponding content in the Fully Disordered Dataset (FDD) [ 46, 54].

The best hybrid models in the classification of vertebral column disorders dataset with two classes, vertebral column disorders dataset with three classes, and lumbar disc dataset were the combination of MSCBAW and k-NN classifier, the combination of MSCBAW and RBF NN classifier, and the combination of MSCBAW and SVM classifier, respectively.

One of the datasets, Statlog heart disease, contains nominal, discrete and real-valued vectors while the other one, BUPA liver disorders dataset, consists of purely real-valued vectors.

One caveat is that the dataset we created may be slightly different from the official disorder dataset used in CASP7 evaluation [ 17].

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.

Thus, in this paper, we first create a large disorder dataset to evaluate the specificity-sensitivity relationship of a state of the art tool, DISpro [ 2].

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.

We also consider a subset of genes involved in monogenic disorders, obtained from Cai et al. [ 22]; this consists of 694 disease genes, 641 of which have a functional annotation ("monogenic disorders" dataset).

For example for cluster X, the R R i is given by RR i = 3 i ∈ X 1 otherwise The results of the four different cluster detection techniques when applied to a bowel disorder dataset in the province of Manitoba, Canada, from 2001 to 2010 are shown and compared in this section.

Figure 4 represents this as the percentages of proteins with ≥ 30 consecutive residues predicted to be disordered in datasets of proteins associated with all four diseases.