MHCPre

This model based on deep learning method can be used to predict peptide binding MHC class II molecules. The advantage of this model is to ignore the length of peptide. In other words, the same model can be used to predict different peptides with different length. We have trained different models for 29 alleles, including 27 human alleles and 2 mouse alleles.

Step1: Input peptide sequence
Enter peptide sequence(s)

or
Example
Step2: Select a species and Allele(s)
Species
Allele(s) or
Example
Step3: Set output
Output Value

All steps to use the model to predict peptide binding MHC class I are as follow:

  • To paste a peptide sequence into the text area, or to upload a file containing some peptide sequences.
  • To select a species.
  • To select allele or to upload a file containing some alleles.
  • To select a output types including ic50 or score.
  • This dataset including 29 allele subdatasets, including 27 hunman alleles and 2 mouse alleles. Every dataset contains four files, including training set, test set, validation set and independent test set. We also supply python code of our biLSTM models. Please download datasets by clicking the link below:

    Human
    Mouse

    We appreciate your comments to make our website more complete in the future, please contact:

    Yan Guo, Ph.D, Yaguo@salud.unm.edu
    Limin Jiang, M.S., jianglm@tju.edu.cn