Domain Combination based Protein-Protein Interaction Prediction (DCPPIP) method is revealed to show outstanding prediction accuracy in Yeast proteins. However, it is not yet apparent whether the method is still valid and can achieve comparable prediction accuracy for the proteins in other species. In this paper, we report the validation results of applying the DCPPIP method for Fly and Human proteins.
View Article and Find Full Text PDFIn this paper, we propose a probabilistic framework to predict the interaction probability of proteins. The notion of domain combination and domain combination pair is newly introduced and the prediction model in the framework takes domain combination pair as a basic unit of protein interactions to overcome the limitations of the conventional domain pair based prediction systems. The framework largely consists of prediction preparation and service stages.
View Article and Find Full Text PDFWith the recognition of the importance of computational approach for protein-protein interaction prediction, many techniques have been developed to computationally predict protein-protein interactions. However, few techniques are actually implemented and announced in service form for general users to readily access and use the techniques. In this paper, we design and implement a protein interaction prediction service system based on the domain combination based protein-protein interaction prediction technique, which is known to show superior accuracy to other conventional computational protein-protein interaction prediction methods.
View Article and Find Full Text PDFWith 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 techniques still have many limitations when used in real fields. They usually suffer from low accuracy in prediction and do not provide any interaction possibility ranking method for multiple protein pairs.
View Article and Find Full Text PDF