A large-scale prediction of protein-protein interactions based on random forest and matrix of sequence

Protein-protein interaction (PPIs) is an important part of many life activities in organisms, and the prediction protein-protein interactions closely related to protein function, disease occurrence, treatment. In order optimize performance interactions, here a RT-MOS model was constructed based on Random Forest (RF) Matrix Sequence (MOS) predict interactions. Firstly, MOS used encode sequences into 29-dimensional feature vector; Then, build random forest, optimized evaluated using test set; Finally, for prediction. The experimental results show that accuracy rates benchmark dataset non-redundant are 97.18% 91.34%, respectively, accuracies four external datasets C.elegans, Drosophila, E.coli H.sapiens 96.21%, 97.86%, 97.54% 97.75%, respectively. Compared with existing methods, it found superior methods. has advantages saving time, preventing overfitting high accuracy, suitable large-scale PPIs