Peptide Ranker

Description

PeptideRanker is a server for the prediction of bioactive peptides based on a novel N-to-1 neural network (described here). PeptideRanker aims to determine for a set of peptides the likelihood that they are bioactive. The peptides can simply be entered into the text box, and will be ranked according to the algorithm's belief that they resemble a bioactive peptide. It does not break down the sequence to look for subsequences within the peptide.

Input

A list of peptide sequences that the user wants to determine whether or not they are bioactive.

Output:

A ranked list of the input peptides, scored by PeptideRanker. The score is not a prediction of the degree of bioactivity but a prediction of how likely the peptide is to be bioactive.

Pages:

  • Paper
  • Training Datasets available upon request to: Bioware user group
  • Help
  • If you use this service please cite:
    Mooney C, Haslam NJ, Pollastri G, Shields DC (2012) Towards the Improved Discovery and Design of Functional Peptides: Common Features of Diverse Classes Permit Generalized Prediction of Bioactivity. PLoS ONE 7(10): e45012.

Enter peptide amino acid one-letter sequences


One peptide per line. Max length 150 residues per peptide.
If a peptide is broken across multiple lines, each line will be treated as a separate peptide
( Example | Clear)