کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5372174 | 1388865 | 2007 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Novel two-stage hybrid neural discriminant model for predicting proteins structural classes
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی تئوریک و عملی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Novel two-stage hybrid neural discriminant model for predicting proteins structural classes Novel two-stage hybrid neural discriminant model for predicting proteins structural classes](/preview/png/5372174.png)
چکیده انگلیسی
In order to establish novel hybrid neural discriminant model, linear discriminant analysis (LDA) was used at the first stage to evaluate the contribution of sequence parameters in determining the protein structural class. An in-house program generated parameters including single amino acid and all dipeptide composition frequencies for 498 proteins came from Zhou [An intriguing controversy over protein structural class prediction, J. Protein Chem. 17(8) (1998) 729-738]. Then, 127 statistically effective parameters were selected by stepwise LDA and were used as inputs of the artificial neural networks (ANNs) to build a two-stage hybrid predictor. In this study, self-consistency and jackknife tests were used to verify the performance of this hybrid model, and were compared with some of prior works. The results showed that our two-stage hybrid neural discriminant model approach is very promising and may play a complementary role to the existing powerful approaches.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biophysical Chemistry - Volume 128, Issue 1, June 2007, Pages 87-93
Journal: Biophysical Chemistry - Volume 128, Issue 1, June 2007, Pages 87-93
نویسندگان
Samad Jahandideh, Parviz Abdolmaleki, Mina Jahandideh, Ebrahim Barzegari Asadabadi,