Different protein-protein interface patterns predicted by different machine learning methods.

Journal: Scientific reports
Published Date:

Abstract

Different types of protein-protein interactions make different protein-protein interface patterns. Different machine learning methods are suitable to deal with different types of data. Then, is it the same situation that different interface patterns are preferred for prediction by different machine learning methods? Here, four different machine learning methods were employed to predict protein-protein interface residue pairs on different interface patterns. The performances of the methods for different types of proteins are different, which suggest that different machine learning methods tend to predict different protein-protein interface patterns. We made use of ANOVA and variable selection to prove our result. Our proposed methods taking advantages of different single methods also got a good prediction result compared to single methods. In addition to the prediction of protein-protein interactions, this idea can be extended to other research areas such as protein structure prediction and design.

Authors

  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Yongxiao Yang
    Mathematics Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, 100872, China.
  • Jianxin Yin
    Center for Applied Statistics and School of Statistics, Renmin University of China, Beijing, 100872, China. jyin@ruc.edu.cn.
  • Xinqi Gong