Inference of Protein-Protein Interactions by Unlikely Profile Pair

We note that a set of statistically “unusual” proteinprofile pairs in experimentally determined database of protein-protein interactions can typify protein-protein interactions, and propose a novel method called PICUPP that sifts such protein-profile pairs using a statistical simulation. It is demonstrated that unusual Pfam and InterPro profile pairs can be extracted from the DIP database using a bootstrapping approach. We particularly illustrate that such protein-profile pairs can be used for predicting putative pairs of interacting proteins. Their prediction accuracies are around 86% and 90% when InterPro and Pfam profiles are used, respectively at 75% confidence level.

• Type: Conference
• Year: 2003
• Where: ICDM
• Authors: Byung-Hoon Park, George Ostrouchov, Gong-Xin Yu, Al Geist, Andrey Gorin, Nagiza F. Samatova
• Keywords: Data Mining, ICDM 2003, InterPro Profile Pairs, Protein-profile Pairs, Protein-protein Interactions