DocumentCode :
2781766
Title :
Mining association rules from HIV-human protein interactions
Author :
Mukhopadhyay, Anirban ; Maulik, Ujjwal ; Bandyopadhyay, Sanghamitra ; Eils, Roland
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of Kalyani, Kalyani, India
fYear :
2010
fDate :
16-18 Dec. 2010
Firstpage :
344
Lastpage :
348
Abstract :
Identifying possible viral-host protein-protein interactions is an important and useful approach in developing new drugs targeting those interactions. In this article, a recently published dataset containing records of interactions between a set of HIV-1 proteins and a set of human proteins has been analyzed using association rule mining. The main objective is to identify a set of association rules among the human proteins with high confidence. The well-known Apriori algorithm has been utilized for discovering the association rules. Moreover, we have predicted some new viral-human interactions based on the discovered association rules.
Keywords :
bioinformatics; data mining; drugs; microorganisms; molecular biophysics; proteins; HIV-1 proteins; HIV-human protein interactions; a priori algorithm; association rule mining; drugs; viral-host protein-protein interactions; Association rules; Bioinformatics; Humans; Itemsets; Proteins; Apriori algorithm; HIV-1-human interaction; Protein-protein interaction; association rule mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems in Medicine and Biology (ICSMB), 2010 International Conference on
Conference_Location :
Kharagpur
Print_ISBN :
978-1-61284-039-0
Type :
conf
DOI :
10.1109/ICSMB.2010.5735401
Filename :
5735401
Link To Document :
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