The University of Kansas Proteomics Service (KUPS) provides high-quality protein-protein interaction (PPI) datasets for researchers who are interested in eulicidating PPIs with 'in silico' methods.

KUPS now combines three manually curated PPI databases (i.e, IntAct, MINT and HPRD ) with features and annotations retrieved from UniProt , Position Specific Scoring Matrix (PSSM) with non-redundent database from NCBI PSI-BLAST , and amino acid scaling features from the Amino Acid Index database .

Positive training examples can be filtered by their host species, interaction type (e.g. targetting only antigen-antibody interactions), experimental derivation (e.g. filter out interactions results from two-hybrid) (see how to use it).

Negative training examples can be generated by four different methods: uniform random pairs, functionally dissimilar pair, spatially separate pairs and non-interacting domain pairs. (see their definitions and usages).

KUPS provides serveral features that can be used for creating train/test data such as protein sequences, Position Specific Score Matrix (PSSM), physicochemical/biochemical scales from AAindex and so on(see how to use it).


This work was supported by National Science Foundation CAREER Award IIS-0644366 and the associated REU.


  • KUPS will be closed during May 29-30, 2012 due to updating DB servers
  • If you cannot get any results from KUPS then please use 'Use All' options for both 'Interaction Types' and 'Detection Methods' first and then narrow down the filtering options < more>

  • KUPS is published in Journal of Nucleic Acids Research (Database issue). Please look at here to get more information about citing KUPS. (October 18,2010)
  • KUPS keeps your dataset for three days. Please read here how you can track your datasets. (August 10, 2010)

  • Browser compatible issues have been solved, but we still recommend using Firefox instead of using IEexplorer. If you find any problem, please let us know (August 8, 2010)

  • Advanced AAindex search(ver 1.0) is launched. (July 1, 2010)

  • WANTED : We are looking for high quality datasets related to protein sequence-based in silico methods. If you would like to share your datasets, please contact us