Prediction of protein functions based on function-function correlation relations

Authors:
Ka-Lok Ng;Jin-Shuei Ciou;Chien-Hung Huang
Affiliations:
Department of Bioinformatics, Asia University, 500 Lioufeng Road, Wufeng Shiang, Taichung 41354, Taiwan;Department of Bioinformatics, Asia University, 500 Lioufeng Road, Wufeng Shiang, Taichung 41354, Taiwan;Department of Computer Science and Information Engineering, National Formosa University, 64, Wen-Hwa Road, Hu-wei, Yun-Lin 632, Taiwan
Venue:
Computers in Biology and Medicine
Year:
2010

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Abstract

A protein function pair approach, based on protein-protein interaction (PPI) data, is proposed to predict protein functions. Randomization tests are performed on the PPI dataset, which resulted in a protein function correlation scoring value which is used to rank the relative importance of a function pair. It has been found that certain classes of protein functions tend to be correlated together. Scoring values of these correlation pairs allow us to predict the functionality of a protein given that it interacts with proteins having well-defined function annotations. The jackknife test is used to validate the function pair method. The protein function pair approach achieves a prediction sensitivity comparable to an approach using more sophisticated method. The main advantages of this approach are as follows: (i) a set of function-function correlation relations are derived and intuitive biological interpretation can be achieved, and (ii) its simplicity, only two parameters are needed.