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Predicting Endoplasmic Reticulum Resident Proteins Using Auto-Cross Covariance Transformation With a U-Shaped Residue Weight-Transfer Function.
- Source :
-
Frontiers in genetics [Front Genet] 2019 Dec 20; Vol. 10, pp. 1231. Date of Electronic Publication: 2019 Dec 20 (Print Publication: 2019). - Publication Year :
- 2019
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Abstract
- Background: The endoplasmic reticulum (ER) is an important organelle in 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 the ER are called ER-resident proteins. These proteins are closely related to the biological functions of the ER. The difference between the ER-resident proteins and other non-resident proteins should be carefully studied. Methods: We developed a support vector machine (SVM)-based method. We developed a U-shaped weight-transfer function and used it, along with the positional-specific physiochemical properties (PSPCP), to integrate together sequence order information, signaling peptides information, and evolutionary information. Result: 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 of identifying ER-resident proteins.<br /> (Copyright © 2019 Miao, Zhao, Li, Gao and Du.)
Details
- Language :
- English
- ISSN :
- 1664-8021
- Volume :
- 10
- Database :
- MEDLINE
- Journal :
- Frontiers in genetics
- Publication Type :
- Academic Journal
- Accession number :
- 31921288
- Full Text :
- https://doi.org/10.3389/fgene.2019.01231