This model based on deep learning method can be used to predict peptide binding MHC class I 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 66 alleles,
including 49 human alleles, three mouse alleles, eight macaque alleles, five chimpanzee alleles and one rat allele.
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 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.
Dataset and code download
This dataset including 67 allele subdatasets, including 49 hunman alleles and 18 other species 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: