کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8876932 | 1623773 | 2018 | 31 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC
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موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم کشاورزی و بیولوژیک (عمومی)
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چکیده انگلیسی
Results of SVM experiments with and without oversampling gained by Jackknife tests show that oversampling methods have successfully decrease the imbalance of data sets, and the prediction accuracy of each class in each dataset is higher than 88.9%. With comparison with other protein subcellular localization methods, the method in this work reaches the best performance. The overall accuracies of ZD98, CL317 and ZW225 are 93.2%, 96.00% and 92.15% respectively, which are 2.4%, 8.0% and 8.2% higher than the best methods in the comparison. The excellent overall accuracy gained by the proposed method indicates that the feature representation and selection capture useful information of protein sequence and oversampling methods successfully solve the imbalance of sample numbers in SVM classification.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Theoretical Biology - Volume 437, 21 January 2018, Pages 239-250
Journal: Journal of Theoretical Biology - Volume 437, 21 January 2018, Pages 239-250
نویسندگان
Shengli Zhang, Xin Duan,