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In computational proteomics, the peptide identification via interpreting its tandem mass spectrum is an important issue. The classification of b and y ions in the spectrum plays a vital role for improving the accuracy of most existing algorithms. To solve this problem, a classification method based on frequent pattern mining and decision tree is proposed in this paper. First a dataset is established...
In computational proteomics, inferring the peptide sequence from its tandem mass spectrum is an important issue. Several algorithms have been proposed to solve this problem. However, few algorithms make good use of the intensity information of the ions. In this paper, a novel scoring strategy is proposed based on kNN technique for identifying peptide by use of tandem mass spectra. First the intensity...
De novo peptide sequencing is especially useful in the identification of unknown proteins. A class of efficient models on de novo peptide interpretation have been proposed recently based on graph theory. However, majority of the graph-based models convert each peak to multiple nodes in the graph due to unknown ion types. This directly results in the decrease of the efficiency and accuracy of peptide...
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