Data mining has been entered in several areas such as medical science and bioinformatics. Proteins are present in all living things. Because of numerous similarities between mice and humans physiology, Protein analysis and implementing various experiments with a focus on this substance in mice can put a lot of information at the disposal of mankind. The main purpose of this study is predicting and Estimation of protein secondary structure by providing an intelligent model. This model is based on Machine learning strategy. Thus, data mining approaches and use those to display the protein secondary structure as Data_Cortex_Nuclear that belongs to the Mice was investigated. Implementation algorithms has been done with Weka and MATLAB software. The results of implementation of algorithms were compared with each other. Finally, by doing a comparative analysis, random forests had the highest accuracy and efficiency.
