Predicting antifreeze proteins with weighted generalized dipeptide composition and multi-regression feature selection ensemble.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Antifreeze proteins (AFPs) are a group of proteins that inhibit body fluids from growing to ice crystals and thus improve biological antifreeze ability. It is vital to the survival of living organisms in extremely cold environments. However, little research is performed on sequences feature extraction and selection for antifreeze proteins classification in the structure and function prediction, which is of great significance.

Authors

  • Shunfang Wang
  • Lin Deng
    Department of Computer Science and Engineering, School of Information Science and Engineering, Yunnan University, Kunming, 650504, China.
  • Xinnan Xia
    Department of Computer Science and Engineering, School of Information Science and Engineering, Yunnan University, Kunming, 650504, China. xiaxinnan1@163.com.
  • Zicheng Cao
  • Yu Fei
    School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming 650221, PR China. Electronic address: feiyukm@aliyun.com.