Random Forest Algorithm in Prediction of Protein Subcellular Localization

Proteins perform their function in subcellulars. Only in specific places, proteins can play their specific functions, and maintain the normal life activities. It is very important to determine the subcellular location of proteins accurately. Protein feature extraction and prediction classification are two key steps in protein subcellular location prediction. In this study, Pseudo Amino Acid Composition model, Amino Acid Physicochemical Property Composition model and Entropy Density model were used to extract feature. Combining the random forest classification model to complete the prediction of protein subcellular localization, the prediction accuracy was greatly improved.