کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1934156 1050634 2009 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Prediction of protein–protein interactions based on PseAA composition and hybrid feature selection
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی زیست شیمی
پیش نمایش صفحه اول مقاله
Prediction of protein–protein interactions based on PseAA composition and hybrid feature selection
چکیده انگلیسی

Based on pseudo amino acid (PseAA) composition and a novel hybrid feature selection frame, this paper presents a computational system to predict the PPIs (protein–protein interactions) using 8796 protein pairs. These pairs are coded by PseAA composition, resulting in 114 features. A hybrid feature selection system, mRMR–KNNs–wrapper, is applied to obtain an optimized feature set by excluding poor-performed and/or redundant features, resulting in 103 remaining features. Using the optimized 103-feature subset, a prediction model is trained and tested in the k-nearest neighbors (KNNs) learning system. This prediction model achieves an overall accurate prediction rate of 76.18%, evaluated by 10-fold cross-validation test, which is 1.46% higher than using the initial 114 features and is 6.51% higher than the 20 features, coded by amino acid compositions. The PPIs predictor, developed for this research, is available for public use at http://chemdata.shu.edu.cn/ppi.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biochemical and Biophysical Research Communications - Volume 380, Issue 2, 6 March 2009, Pages 318–322
نویسندگان
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