کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4497339 1318929 2010 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Lysine acetylation sites prediction using an ensemble of support vector machine classifiers
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم کشاورزی و بیولوژیک (عمومی)
پیش نمایش صفحه اول مقاله
Lysine acetylation sites prediction using an ensemble of support vector machine classifiers
چکیده انگلیسی
Lysine acetylation is an essentially reversible and high regulated post-translational modification which regulates diverse protein properties. Experimental identification of acetylation sites is laborious and expensive. Hence, there is significant interest in the development of computational methods for reliable prediction of acetylation sites from amino acid sequences. In this paper we use an ensemble of support vector machine classifiers to perform this work. The experimentally determined acetylation lysine sites are extracted from Swiss-Prot database and scientific literatures. Experiment results show that an ensemble of support vector machine classifiers outperforms single support vector machine classifier and other computational methods such as PAIL and LysAcet on the problem of predicting acetylation lysine sites. The resulting method has been implemented in EnsemblePail, a web server for lysine acetylation sites prediction available at http://www.aporc.org/EnsemblePail/.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Theoretical Biology - Volume 264, Issue 1, 7 May 2010, Pages 130-135
نویسندگان
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