15 October 2012 Feature selection from short amino acid sequences in phosphorylation prediction problem
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Proceedings Volume 8454, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2012; 84541W (2012) https://doi.org/10.1117/12.2001270
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2012, 2012, Wilga, Poland
Abstract
The paper describes solution of feature selection from amino acid sequences in phosphorylation prediction problem. We show that even for short sequences the variable selection leads to better classification performance. Moreover, the final simplicity of models allows for better data understanding and can be used by an expert for further analysis. The feature selection process is divided into two parts: i) the classification tree is used for finding the most relevant positions in amino acid sequences, ii) then the contrast pattern kernel is applied for pattern selection. This work summarizes the research made on classification of short amino acid sequences. The results of the research allowed us to propose a general scheme of amino acid sequence analysis.
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Jakub Węcławski, Jakub Węcławski, Stanisław Jankowski, Stanisław Jankowski, Zbigniew Szymański, Zbigniew Szymański, } "Feature selection from short amino acid sequences in phosphorylation prediction problem", Proc. SPIE 8454, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2012, 84541W (15 October 2012); doi: 10.1117/12.2001270; https://doi.org/10.1117/12.2001270
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