Protein-protein interaction prediction based on association rules of protein functional regions

Fei-Hung Hung; Chiu Hung-Wen

doi:10.1109/ICICIC.2007.466

Protein-protein interaction prediction based on association rules of protein functional regions

Fei-Hung Hung, Chiu Hung-Wen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Citations (Scopus)

Abstract

In cells, protein-protein interaction (PPI) controls the biological process. For decoding mechanism of diseases, investigators attempt to predict PPI. Recently PPI is a popular subject in bioinformatics. Functional regions of compact protein structure interact with others. Nearly a lot of PPI-related tools were produced and available. Furthermore, researchers applied computational methods with statistic methods to predict PPIs. In some researches, the investigators had tried to use it to find out the relationship of protein pair in PPI. In this paper, we collected proteins and PPI data from DIP and IntAct. Next, the data of functional regions was downloaded from UNIPROT. They were integrated into our database. Moreover, two modules of PPI prediction were established with Saccharomyces cerevisiae (yeast) and Drosophila melanogaster (fruit fly) by an association rule tool. We applied two different species' PPIs for evidence of the two modules.

Original language	English
Title of host publication	Second International Conference on Innovative Computing, Information and Control, ICICIC 2007
DOIs	https://doi.org/10.1109/ICICIC.2007.466
Publication status	Published - 2008
Event	2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007 - Kumamoto, Japan Duration: Sept 5 2007 → Sept 7 2007

Other

Other	2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007
Country/Territory	Japan
City	Kumamoto
Period	9/5/07 → 9/7/07

ASJC Scopus subject areas

General Computer Science
Mechanical Engineering

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10.1109/ICICIC.2007.466

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Hung, F-H & Hung-Wen, C 2008, Protein-protein interaction prediction based on association rules of protein functional regions. in Second International Conference on Innovative Computing, Information and Control, ICICIC 2007., 4428001, 2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007, Kumamoto, Japan, 9/5/07. https://doi.org/10.1109/ICICIC.2007.466

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title = "Protein-protein interaction prediction based on association rules of protein functional regions",

abstract = "In cells, protein-protein interaction (PPI) controls the biological process. For decoding mechanism of diseases, investigators attempt to predict PPI. Recently PPI is a popular subject in bioinformatics. Functional regions of compact protein structure interact with others. Nearly a lot of PPI-related tools were produced and available. Furthermore, researchers applied computational methods with statistic methods to predict PPIs. In some researches, the investigators had tried to use it to find out the relationship of protein pair in PPI. In this paper, we collected proteins and PPI data from DIP and IntAct. Next, the data of functional regions was downloaded from UNIPROT. They were integrated into our database. Moreover, two modules of PPI prediction were established with Saccharomyces cerevisiae (yeast) and Drosophila melanogaster (fruit fly) by an association rule tool. We applied two different species' PPIs for evidence of the two modules.",

author = "Fei-Hung Hung and Chiu Hung-Wen",

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AU - Hung, Fei-Hung

AU - Hung-Wen, Chiu

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AB - In cells, protein-protein interaction (PPI) controls the biological process. For decoding mechanism of diseases, investigators attempt to predict PPI. Recently PPI is a popular subject in bioinformatics. Functional regions of compact protein structure interact with others. Nearly a lot of PPI-related tools were produced and available. Furthermore, researchers applied computational methods with statistic methods to predict PPIs. In some researches, the investigators had tried to use it to find out the relationship of protein pair in PPI. In this paper, we collected proteins and PPI data from DIP and IntAct. Next, the data of functional regions was downloaded from UNIPROT. They were integrated into our database. Moreover, two modules of PPI prediction were established with Saccharomyces cerevisiae (yeast) and Drosophila melanogaster (fruit fly) by an association rule tool. We applied two different species' PPIs for evidence of the two modules.

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Protein-protein interaction prediction based on association rules of protein functional regions

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