کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
14950 1362 2016 6 صفحه PDF ندارد دانلود رایگان
عنوان انگلیسی مقاله
A computational model for predicting fusion peptide of retroviruses
ترجمه فارسی عنوان
یک مدل محاسباتی برای پیش بینی پپتید همجوشی retroviruses
کلمات کلیدی
پیش بینی دامنه پپتید فیوژن؛ روش مخفی مارکف؛ مقایسه شباهت
Fusion peptide domain prediction; Hidden Markov Method; Similarity comparison
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی بیو مهندسی (مهندسی زیستی)
چکیده انگلیسی


• A novel computational model for predicting fusion peptide of retroviruses was proposed.
• A software tool named FP_predict.exe has been developed.
• A large number of new putative FPs of five typical retroviruses were predicted.
• Property, motif and evolutionary relationship about FP were computed and discussed.

As a pivotal domain within envelope protein, fusion peptide (FP) plays a crucial role in pathogenicity and therapeutic intervention. Taken into account the limited FP annotations in NCBI database and absence of FP prediction software, it is urgent and desirable to develop a bioinformatics tool to predict new putative FPs (np-FPs) in retroviruses. In this work, a sequence-based FP model was proposed by combining Hidden Markov Method with similarity comparison. The classification accuracies are 91.97% and 92.31% corresponding to 10-fold and leave-one-out cross-validation. After scanning sequences without FP annotations, this model discovered 53,946 np-FPs. The statistical results on FPs or np-FPs reveal that FP is a conserved and hydrophobic domain. The FP software programmed for windows environment is available at https://sourceforge.net/projects/fptool/files/?source=navbar.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Biology and Chemistry - Volume 61, April 2016, Pages 245–250
نویسندگان
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