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Protein Interaction Possibility Ranking Method based on Domain Combination  

Han Dong-Soo (한국정보통신대학교 공학부)
Kim Hong-Song (한국정보통신대학교 공학부)
Jong Woo-Hyuk (한국정보통신대학교 공학부)
Lee Sung-Doke (한국정보통신대학교 공학부)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.11, no.5, 2005 , pp. 427-435 More about this Journal
Abstract
With the accumulation of protein and its related data on the Internet, many domain based computational techniques to predict protein interactions have been developed. However, most of the techniques still have many limitations to be used in real fields. They usually suffer from a low accuracy problem in prediction and do not provide any interaction possibility ranking method for multiple protein pairs. In this paper, we reevaluate a domain combination based protein interaction prediction method and develop an interaction possibility ranking method for multiple protein pairs. Probability equations are devised and proposed in the framework of domain combination based protein interaction prediction method. Using the ranking method, one can discern which protein pair is more probable to interact with each other than other protein pairs in multiple protein pairs. In the validation of the ranking method, we revealed that there exist some correlations between the interacting probability and the precision of the prediction in case of the protein pair group having the matching PIP(Primary Interaction Probability) values in the interacting or non interacting PIP distributions.
Keywords
Protein protein interaction; Domain combination; Domain combination pair; Prediction model; AP matrix; Protein-protein interaction possibility ranking method.;
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