Table 1 Algorithm for neoantigen prediction

NetMHC-3.0

Artificial neural network-based algorithm for prediction of binding affinity between MHC-I and peptides of length 8–11

[89]

NetMHCpan-3.0

Machine-learning model-based algorithm for prediction of binding affinity between MHC-I and peptides, a pan-specific version

[90]

NetMHCcons

Comprehensive algorithm for prediction of binding affinity between MHC-I and peptides

[41]

NetMHCstab

Artificial neural network-based algorithm for prediction of stability of peptide-MHC-I complex

[91]

PickPocket

Position-specific scoring matrix-based algorithm for prediction of binding affinity between MHC-I and peptides

[92]

FRED2

Epitope prediction for neoantigen

[93]

NetCTL-1.2

Comprehensive prediction algorithm containing proteasome cleavage, TAP transport, and MHC-I binding affinity

[94]

NetCTLpan

The pan-specific version of NetCTL

[95]

NetTepi

Integrated prediction algorithm containing binding affinity, stability of peptide-MHC-I complex, and T cell propensity

[46]

pVAC-Seq

Identification of neoantigen by tumor mutation and expression data

[96]

EpiToolKit

Prediction of MHC-I typing and T cell epitope

[97]

WAPP

Comprehensive prediction algorithm containing proteasome cleavage, TAP transport, and MHC-I binding affinity

[98]