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X. Dai developed the new data fusion method, implemented the two novel data sources in TF target gene prediction, and performed all the simulations.
For the two novel data sources, we also compared their CDFs after shifting with the original ones as shown in Figure 3.
Two novel data sets have been used in this study to exemplify the performance of PhosphOrtholog when compared to PhosphoSitePlus.
The method is based on two novel data structures for rapid screening of large databases: the kD grid and the Multibit tree.
In this study, we applied two novel data analysis methods (regularized regression and random forests) in bioprocess data mining and compared them to multiple linear regression that is commonly applied in relation to statistical design of experiments.
In the following, we present a method for finding all fingerprints B in a database of fingerprints with a Tanimoto coefficient above some query-specific threshold Smin to a query fingerprint A. The method is based on two novel data structures, the kD grid and the Multibit tree, for storing the database of fingerprints.
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In this section, the results of exploring two novel additional data sources, evaluating the new data fusion method and comparison among different data source combinations in TF target gene prediction are sequentially reported and discussed.
Two novel reversible data hiding methods based on the depth no-synthesis-error (D-NOSE) model are proposed to embed hidden data in the depth maps of 3D images.
In this paper, we present an efficient method for the screening problem, which is based on an extension of an upper bound given in [ 6] and two novel tree based data structures for storing and retrieving fingerprints.
We have conducted an evaluation of the performance of these two novel features on EEG data corresponding to motor-imagery.
The proposed SDAACA protocol consists of two novel algorithms: the secure data fragmentation (SDF) and the node joining authorization (NJA).
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