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Feature selection techniques have become an apparent need in many bioinformatics applications. In this article, taking into account the protein-protein interactions in sequence and spatial structure of protein, we propose a new correlation based method to capture these correlations between features to check feature redundancy, and implement a corresponding feature selection algorithm CBPFS. Features...
This paper addresses one of the challenges of machine learning in improving performance through feature selection algorithms (FSAs). Application of FSAs in the bioinformatics domain has become a necessity due to enormous growth of public sequence databases. This paper provides an experimental framework on the use of rough set theory (RST) as FSAs in finding minimal feature subsets for classifying...
Inter-residue interactions play an important role in governing the folding and stability of protein structures. In this work, we have analyzed the contacts between amino acid residues in different folding types of globular proteins and various ranges of folding rates. Based on amino acid contacts a novel parameter, multiple contact index has been developed for understanding protein folding rates....
Visible and near infrared spectroscopy (Vis/NIR) combined with chemometric methods was employed to classify rice wines with different ages. Spectra of 240 wine samples (80 for each year) were collected in the Vis/NIR region (325-1075nm) in the spectroradiometer in transmission mode. Partial least squares (PLS) analysis was applied to extract the principal components (PCs) as new eigenvectors to represent...
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