Prediction of B-cell Linear Epitopes with a Combination of Support Vector Machine Classification and Amino Acid Propensity Identification

@inproceedings{Wang2011PredictionOB,
  title={Prediction of B-cell Linear Epitopes with a Combination of Support Vector Machine Classification and Amino Acid Propensity Identification},
  author={Hsin-Wei Wang and Ya-Chi Lin and Tun-Wen Pai and Hao-Teng Chang},
  booktitle={Journal of biomedicine & biotechnology},
  year={2011}
}
Epitopes are antigenic determinants that are useful because they induce B-cell antibody production and stimulate T-cell activation. Bioinformatics can enable rapid, efficient prediction of potential epitopes. Here, we designed a novel B-cell linear epitope prediction system called LEPS, Linear Epitope Prediction by Propensities and Support Vector Machine, that combined physico-chemical propensity identification and support vector machine (SVM) classification. We tested the LEPS on four datasets… CONTINUE READING
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