کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
1172674 1491340 2016 6 صفحه PDF سفارش دهید دانلود کنید
عنوان انگلیسی مقاله ISI
Predicting pupylation sites in prokaryotic proteins using semi-supervised self-training support vector machine algorithm
ترجمه فارسی عنوان
پیش بینی سایت های pupylation در پروتئین پروکریوت ها با استفاده از الگوریتم ماشین بردار پشتیبانی نیمه نظارت خودآموز
کلمات کلیدی
اصلاح پس از ترجمه ؛ پاپیلاسیون؛ یادگیری نیمه نظارتی؛ ماشین بردار پشتیبانی؛ پروتئین های پروبیوتیک مانند ubiquitin؛ DOP، deamidase از Pup؛ PafA، عامل پروتئازوم لوازم جانبی A؛ GPS، سیستم پیش بینی مبتنی بر گروه؛
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
چکیده انگلیسی

As one important post-translational modification of prokaryotic proteins, pupylation plays a key role in regulating various biological processes. The accurate identification of pupylation sites is crucial for understanding the underlying mechanisms of pupylation. Although several computational methods have been developed for the identification of pupylation sites, the prediction accuracy of them is still unsatisfactory. Here, a novel bioinformatics tool named IMP–PUP is proposed to improve the prediction of pupylation sites. IMP–PUP is constructed on the composition of k-spaced amino acid pairs and trained with a modified semi-supervised self-training support vector machine (SVM) algorithm. The proposed algorithm iteratively trains a series of support vector machine classifiers on both annotated and non-annotated pupylated proteins. Computational results show that IMP–PUP achieves the area under receiver operating characteristic curves of 0.91, 0.73, and 0.75 on our training set, Tung's testing set, and our testing set, respectively, which are better than those of the different error costs SVM algorithm and the original self-training SVM algorithm. Independent tests also show that IMP–PUP significantly outperforms three other existing pupylation site predictors: GPS–PUP, iPUP, and pbPUP. Therefore, IMP–PUP can be a useful tool for accurate prediction of pupylation sites. A MATLAB software package for IMP–PUP is available at https://juzhe1120.github.io/.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Analytical Biochemistry - Volume 507, 15 August 2016, Pages 1–6
نویسندگان
, ,