Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1950887 | Biochimica et Biophysica Acta (BBA) - Molecular Cell Research | 2011 | 7 Pages |
It is very challenging and complicated to predict protein locations at the sub-subcellular level. The key to enhancing the prediction quality for protein sub-subcellular locations is to grasp the core features of a protein that can discriminate among proteins with different subcompartment locations. In this study, a different formulation of pseudoamino acid composition by the approach of discrete wavelet transform feature extraction was developed to predict submitochondria and subchloroplast locations. As a result of jackknife cross-validation, with our method, it can efficiently distinguish mitochondrial proteins from chloroplast proteins with total accuracy of 98.8% and obtained a promising total accuracy of 93.38% for predicting submitochondria locations. Especially the predictive accuracy for mitochondrial outer membrane and chloroplast thylakoid lumen were 82.93% and 82.22%, respectively, showing an improvement of 4.88% and 27.22% when other existing methods were compared. The results indicated that the proposed method might be employed as a useful assistant technique for identifying sub-subcellular locations. We have implemented our algorithm as an online service called SubIdent (http://bioinfo.ncu.edu.cn/services.aspx).
Research Highlights► Discrete wavelet transform (DWT) can effectively grasp the core features of the subcellular locations. ► A new method, in which SVM combines with DWT, is developed to predict the subcellular locations. ► The proposed approach can remarkably improve the predictive accuracies of the submitochondria and subchloroplast locations.