AUTHOR=Miao Yang-Yang , Zhao Wei , Li Guang-Ping , Gao Yang , Du Pu-Feng 

TITLE=Predicting Endoplasmic Reticulum Resident Proteins Using Auto-Cross Covariance Transformation With a U-Shaped Residue Weight-Transfer Function

JOURNAL=Frontiers in Genetics

VOLUME=Volume 10 - 2019

YEAR=2019

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2019.01231

DOI=10.3389/fgene.2019.01231

ISSN=1664-8021

ABSTRACT=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.