Predicting Endoplasmic Reticulum Resident Proteins Using Auto-Cross Covariance Transformation With a U-Shaped Residue Weight-Transfer Function - Miao, Yang-Yang; Zhao, Wei; Li, Guang-Ping; Gao, Yang; Du, Pu-Feng (Frontiers in Genetics, 2019)
The endoplasmic reticulum (ER) is an important organelle of eukaryotic cells. It is involved in many important biological processes, such as cell metabolism, protein synthesis, and post-translational modification. The proteins that reside within ER are called ER-resident proteins. These proteins are closely related to biological functions of ER. The difference between the ER-resident proteins and other non-resident proteins should be carefully studied. We developed a support vector machine (SVM) based method. We introduced a U-shaped weight transfer function, along with the positional-specific physiochemical properties (PSPCP), to integrate sequence order information, signaling peptides information, and evolutionary information together. Our method achieved over 86% accuracy in a jackknife test. We also achieved roughly 86% sensitivity and 67% specificity in an independent dataset test. Our method is capable to identify ER-resident proteins.