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This paper introduces a Protein Query Language (PQL) for querying protein structures in an expressive yet concise manner. One of the objectives of the paper is to demonstrate how such a language would be beneficial to protein researchers to obtain in-depth protein data from a relational database without extensive SQL knowledge. The language features options such as limiting query results by key protein...
Dimensionality reduction techniques have become a required step when working with bioinformatics datasets. Techniques such as feature selection have been known to not only improve computation time, but to improve the results of experiments by removing the redundant and irrelevant features or genes from consideration in subsequent analysis. Univariate feature selection techniques in particular are...
Feature (gene) selection has become an important and necessary step for combating high dimensionality, a problem found in bioinformatics datasets. Many studies have focused on gene selection, examining both the design of these techniques and the classification performance of prediction models built using these techniques. However, it is only recently that any work has focused on the robustness or...
Ensemble feature selection has recently become a topic of interest for researchers, especially in the area of bioinformatics. The benefits of ensemble feature selection include increased feature (gene) subset stability and usefulness as well as comparable (or better) classification performance compared to using a single feature selection method. However, existing work on ensemble feature selection...
Dimensionality-reducing techniques such as gene selection have become commonplace in order to reduce the high dimensionality found within bioinformatics datasets such as DNA microarray datasets. The degree of dimensionality is reduced by identifying and removing redundant and irrelevant features or genes and leaving only an optimum subset of features for subsequent analysis. However, a number of feature...
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