کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5666683 1591542 2017 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multilevel ensemble model for prediction of IgA and IgG antibodies
موضوعات مرتبط
علوم زیستی و بیوفناوری ایمنی شناسی و میکروب شناسی ایمونولوژی
پیش نمایش صفحه اول مقاله
Multilevel ensemble model for prediction of IgA and IgG antibodies
چکیده انگلیسی


- A novel multilevel ensemble model is developed for prediction of antibodies IgG and IgA.
- In this ensemble approach, seven different machine learning models are combined to predict variable length of epitopes (4 to 50).
- The proposed model of IgG specific epitopes achieves 94.43% of accuracy and IgA specific epitopes achieves 97.56% of accuracy with repeated 10-fold cross validation.
- The proposed model is compared with the existing system i.e. Igpred model and outcome of proposed model is improved.

Identification of antigen for inducing specific class of antibody is prime objective in peptide based vaccine designs, immunodiagnosis, and antibody productions. It's urge to introduce a reliable system with high accuracy and efficiency for prediction. In the present study, a novel multilevel ensemble model is developed for prediction of antibodies IgG and IgA. Epitope length is important in training the model and it is efficient to use variable length of epitopes. In this ensemble approach, seven different machine learning models are combined to predict variable length of epitopes (4 to 50). The proposed model of IgG specific epitopes achieves 94.43% of accuracy and IgA specific epitopes achieves 97.56% of accuracy with repeated 10-fold cross validation. The proposed model is compared with the existing system i.e. IgPred model and outcome of proposed model is improved.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Immunology Letters - Volume 184, April 2017, Pages 51-60
نویسندگان
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