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Using Logistic Regression Method to Predict Protein Function from Protein-Protein Interaction Data

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6 Author(s)
Qingshan Ni ; Coll. of Electro-Mechanic & Autom., Nat. Univ. of Defense Technol., Changsha, China ; Zheng-Zhi Wang ; Qingjuan Han ; Gangguo Li
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Protein function determination is one of the most important issues in biology research. In this paper, a new method, which is based on logistic regression method, is introduced to predict protein function from protein-protein interaction data. In the proposed method, associations among different functions are taken into account by representing a protein using all the functional annotations of its interaction protein partners. We apply our method to a constructed data set for yeast based upon protein function classifications of FunCat scheme and upon the interaction networks collected from BioGrid. The results obtained by 3-fold cross-validation test show that the proposed method can obtain desirable results for protein function prediction and outperforms some existing approaches based on protein-protein interaction data.

Published in:

Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on

Date of Conference:

11-13 June 2009