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Chu-Ling Ko

Department of Computer Science, National Chiao Tung University, 1001 University Rd, Hsinchu, Taiwan

Publications

  • Original Article   
    Computational Ensemble Approach for Immune System Study: Conformational B-cell Epitope Prediction
    Author(s): Yuh-Jyh Hu*, Shun-Ning You and Chu-Ling Ko

    Various tools have been developed to predict B-cell epitopes. We proposed a multistrategy approach by integrating two ensemble learning techniques, namely bagging and meta-decision tree, with a threshold-based cost-sensitive method. By exploiting the synergy among multiple retrainable inductive learners, it directly learns a tree-like classification architecture from the data, and is not limited by a prespecified structure. In addition, we introduced a new three-dimensional sphere-based structural feature to improve the window-based linear features for increased residue description. We performed independent and cross-validation tests, and compared with previous ensemble meta-learners and state-of-the-art B-cell epitope prediction tools using bound-state and unboundstate antigens. The results demonstrated the superior performance of the bagging meta-decision tree approach compared with.. Read More»
    DOI: 10.24105/ejbi.2018.14.1.3