Inference of Protein-Protein Interactions by Unlikely Profile Pair

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http://doi.ieeecomputersociety.org/10.1109/ICDM.2003.1251020

Third IEEE International Conference o ...

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	Byung-Hoon Park, George Ostrouchov, Gong-Xin Yu, Al Geist, Andrey Gorin, Nagiza F. Samatova, "Inference of Protein-Protein Interactions by Unlikely Profile Pair," Data Mining, IEEE International Conference on, pp. 735, Third IEEE International Conference on Data Mining (ICDM'03), 2003.

	BibTex	x
	@article{ 10.1109/ICDM.2003.1251020, author = {Byung-Hoon Park and George Ostrouchov and Gong-Xin Yu and Al Geist and Andrey Gorin and Nagiza F. Samatova}, title = {Inference of Protein-Protein Interactions by Unlikely Profile Pair}, journal ={Data Mining, IEEE International Conference on}, volume = {0}, year = {2003}, isbn = {0-7695-1978-4}, pages = {735}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2003.1251020}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Mining, IEEE International Conference on TI - Inference of Protein-Protein Interactions by Unlikely Profile Pair SN - 0-7695-1978-4 SP EP A1 - Byung-Hoon Park, A1 - George Ostrouchov, A1 - Gong-Xin Yu, A1 - Al Geist, A1 - Andrey Gorin, A1 - Nagiza F. Samatova, PY - 2003 KW - null VL - 0 JA - Data Mining, IEEE International Conference on ER -

Byung-Hoon Park, Oak Ridge National Laboratory

George Ostrouchov, Oak Ridge National Laboratory

Gong-Xin Yu, Oak Ridge National Laboratory

Al Geist, Oak Ridge National Laboratory

Andrey Gorin, Oak Ridge National Laboratory

Nagiza F. Samatova, Oak Ridge National Laboratory

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.

Citation:

Byung-Hoon Park, George Ostrouchov, Gong-Xin Yu, Al Geist, Andrey Gorin, Nagiza F. Samatova, "Inference of Protein-Protein Interactions by Unlikely Profile Pair," icdm, pp.735, Third IEEE International Conference on Data Mining (ICDM'03), 2003

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