@inproceedings{8e3c9c3f86b34435b4c958e0693b75db,
title = "Inference of protein-protein interactions by unlikely profile pair",
abstract = "We note that a set of statistically {"}unusual{"} protein-profile 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.",
author = "Park, \{Byung Hoon\} and George Ostrouchov and Yu, \{Gong Xin\} and Al Geist and Andrey Gorin and Samatova, \{Nagiza F.\}",
year = "2003",
language = "English",
isbn = "0769519784",
series = "Proceedings - IEEE International Conference on Data Mining, ICDM",
pages = "735--738",
booktitle = "Proceedings - 3rd IEEE International Conference on Data Mining, ICDM 2003",
note = "3rd IEEE International Conference on Data Mining, ICDM '03 ; Conference date: 19-11-2003 Through 22-11-2003",
}