کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1952569 1057215 2010 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Prediction of protein structural class for low-similarity sequences using support vector machine and PSI-BLAST profile
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی زیست شیمی
پیش نمایش صفحه اول مقاله
Prediction of protein structural class for low-similarity sequences using support vector machine and PSI-BLAST profile
چکیده انگلیسی

Knowledge of structural class plays an important role in understanding protein folding patterns. In this study, a simple and powerful computational method, which combines support vector machine with PSI-BLAST profile, is proposed to predict protein structural class for low-similarity sequences. The evolution information encoding in the PSI-BLAST profiles is converted into a series of fixed-length feature vectors by extracting amino acid composition and dipeptide composition from the profiles. The resulting vectors are then fed to a support vector machine classifier for the prediction of protein structural class. To evaluate the performance of the proposed method, jackknife cross-validation tests are performed on two widely used benchmark datasets, 1189 (containing 1092 proteins) and 25PDB (containing 1673 proteins) with sequence similarity lower than 40% and 25%, respectively. The overall accuracies attain 70.7% and 72.9% for 1189 and 25PDB datasets, respectively. Comparison of our results with other methods shows that our method is very promising to predict protein structural class particularly for low-similarity datasets and may at least play an important complementary role to existing methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biochimie - Volume 92, Issue 10, October 2010, Pages 1330–1334
نویسندگان
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