Publications by Type: Journal Article

Journal Article
S. Wan and M. - W. Mak, “Predicting subcellular localization of multi-location proteins by improving support vector machines with an adaptive-decision scheme,” International Journal of Machine Learning and Cybernetics, pp. 1–13, In Press. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “Gram-LocEN: Interpretable prediction of subcellular multi-localization of Gram-positive and Gram-negative bacterial proteins,” Chemometrics and Intelligent Laboratory Systems, vol. 162, pp. 1-9, 2017. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “FUEL-mLoc: Feature-Unified Prediction and Explanation of Multi-Localization of Cellular Proteins in Multiple Organisms,” Bioinformatics, vol. 33, no. 5, pp. 749-750, 2017. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “Transductive Learning for Multi-Label Protein Subchloroplast Localization Prediction,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 14, no. 1, pp. 212-224, 2017. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “Ensemble Linear Neighborhood Propagation for Predicting Subchloroplast Localization of Multi-Location Proteins,” Journal of Proteome Research, vol. 15, no. 12, pp. 4755-4762, 2016. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “Mem-mEN: predicting multi-functional types of membrane proteins by interpretable elastic nets,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 13, no. 4, pp. 706-718, 2016. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “Benchmark data for identifying multi-functional types of membrane proteins,” Data in Brief, vol. 8, pp. 105–107, 2016. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “Mem-ADSVM: a two-layer multi-label predictor for identifying multi-functional types of membrane proteins,” Journal of Theoretical Biology, vol. 398, pp. 32–42, 2016. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “Sparse regressions for predicting and interpreting subcellular localization of multi-label proteins,” BMC Bioinformatics, vol. 17, pp. 97, 2016. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “mLASSO-Hum: A LASSO-based interpretable human-protein subcellular localization predictor,” Journal of Theoretical Biology, vol. 382, pp. 223–234, 2015. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “mPLR-Loc: An adaptive decision multi-label classifier based on penalized logistic regression for protein subcellular localization prediction,” Analytical Biochemistry, vol. 473, pp. 14–27, 2015. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “HybridGO-Loc: Mining hybrid features on gene ontology for predicting subcellular localization of multi-location proteins,” PLoS One, vol. 9, pp. e89545, 2014. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “R3P-Loc: A compact multi-label predictor using ridge regression and random projection for protein subcellular localization,” Journal of Theoretical Biology, vol. 360, pp. 34–45, 2014. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “GOASVM: a subcellular location predictor by incorporating term-frequency gene ontology into the general form of Chou's pseudo-amino acid composition,” Journal of Theoretical Biology, vol. 323, pp. 40–48, 2013. Publisher's Version
S. Wan, M. - W. Mak, S. - Y. Kung, and others, “Semantic similarity over gene ontology for multi-label protein subcellular localization,” Engineering, vol. 5, pp. 68, 2013. Publisher's Version
S. Wan, M. - W. Mak, and S. - Y. Kung, “mGOASVM: Multi-label protein subcellular localization based on gene ontology and support vector machines,” BMC Bioinformatics, vol. 13, pp. 290, 2012. Publisher's Version