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While some approaches utilize information from the entire scene to propose regions of interest, the task of interpreting a particular region or object is still performed independently of other objects and features in the image.
Both approaches utilize information from known kinase active and inactive compounds.
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In this way, the approach utilizes information across a set of arrays to optimize model fit and is thus more efficient than a number of methods that make inferences one probe set at a time [79].
Our NCL-NNE prediction approach utilizes information derived from a single protein structure and its sequence homologs.
In GTA, pairwise distances are employed between adjacent markers only, whereas our approach utilizes information from the whole distance matrix.
In this way, the approach utilizes information across genes and arrays to optimize model fit, and is thus more efficient than a number of methods that make gene inferences one gene at a time.
In comparison, pathway-based approaches that utilize information from multiple loci in a functional unit could produce more stable and robust results than single gene analyses do [7,31].
In our approach, we utilize information on STRING database and expression data to construct a weighted network and to decipher the active networks related to drug resistance using A* search method.
A more attractive approach is to utilize information jointly from both common and rare variants.
Our approach does not utilize information that specifically holds only for the problem studied in this paper.
Some approaches utilize spatial information by considering frames from videos as still image sets without considering their temporal information.
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