How to interpret


How to understand the output
After converting the .csv-file into a spreadsheet (see How to use) it should look like this:


We recommend transforming the data field into a table to easily sort for best predictions.

The columns contain the following information:
  • Position Start: the position of the first amino acid of the predicted peptide within the input sequence
  • Region: the start and end position of the predicted peptide
  • Length: the length of the predicted peptide
  • Sequence: the amino acid sequence of the predicted peptide
  • Algorithm Name: the output values of the respective method

  • "N/A" means that a peptide is not predicted by the server
    e.g. if the server does not perform prediction of the chosen peptide length.


    The output values of the prediction methods are:

  • IC50 in nM (NetMHC methods, IEDB smm and IEDB smmpmbec):
    The lower the value, the stronger the binding affinity.
    Usual thresholds are IC50 ≤ 50nM (strong affinity) and IC50 ≤ 500nM (low affinity).

  • Percentile rank (IEDB recommended and IEDB consensus):
    The lower the value, the higher the chances of binding.
    Usual thresholds are %-rank ≤ 0.5 (strong affinity) and %-rank ≤ 2 (low affinity).

  • Score (SYFPEITHI):
    The higher the binding score, the higher the chances of binding.
    SYFPEITHI does not recommend any threshold.

  • Please see Recommendations for information about increasing prediction sensitivity by using more tolerant thresholds.