Prediction of MHC class II binding peptides based on an iterative learning model

@article{Murugan2005PredictionOM,
  title={Prediction of MHC class II binding peptides based on an iterative learning model},
  author={Naveen Murugan and Yang Dai},
  journal={Immunome Research},
  year={2005},
  volume={1},
  pages={6 - 6}
}
BACKGROUND Prediction of the binding ability of antigen peptides to major histocompatibility complex (MHC) class II molecules is important in vaccine development. The variable length of each binding peptide complicates this prediction. Motivated by a text mining model designed for building a classifier from labeled and unlabeled examples, we have developed an iterative supervised learning model for the prediction of MHC class II binding peptides. RESULTS A linear programming (LP) model was… CONTINUE READING
38 Citations
30 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 38 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 30 references

SVM based method for predicting HLADRB 1 * 0401 binding peptides in an antigen sequence

  • M Bhasin, Raghava GPS
  • 2004

Similar Papers

Loading similar papers…