PPI-Detect

PPI-Detect

Sequence-based Predictor of Protein-Protein Interactions

The prediction of the likelihood of protein-protein interactions (PPI) is a challenging task, especially if amino acid sequences are the only information available. We use a novel procedure for general-purpose numerical encoding of polypeptides, which transforms pairs of amino acid sequences into a machine-learning-friendly vector, whose elements represent numerical descriptors of groups of residues in the proteins. PPI-Detect is a Support-Vector-Machine model for predicting protein-protein and protein-peptide interactions.


How to cite PPI-Detect:

S. Romero‐Molina, Y. B. Ruiz‐Blanco, M. Harms, J. Münch, E. Sanchez‐Garcia. PPI‐Detect: A support vector machine model for sequence‐based prediction of protein–protein interactions J. Comput. Chem. 2019, 1‐10. DOI: 10.1002/jcc.25780

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Please provide at least one sequence (FASTA format) in each of the fields below.

NOTES:
(1) The interaction likelihood will be computed for all the combinatorial pairs between the two sets of sequences.
(2) The size of each job is limited according the following criterion: (number of sequences in panel A) x (number of sequences in panel B) <= 5000


OR

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The file must be in FASTA format. See the help section.


OR

The file must be in FASTA format. See the help section.