A New Method for Recognizing Cytokines Based on Feature Combination and a Support Vector Machine Classifier.

Journal: Molecules (Basel, Switzerland)
Published Date:

Abstract

Research on cytokine recognition is of great significance in the medical field due to the fact cytokines benefit the diagnosis and treatment of diseases, but the current methods for cytokine recognition have many shortcomings, such as low sensitivity and low F-score. Therefore, this paper proposes a new method on the basis of feature combination. The features are extracted from compositions of amino acids, physicochemical properties, secondary structures, and evolutionary information. The classifier used in this paper is SVM. Experiments show that our method is better than other methods in terms of accuracy, sensitivity, specificity, F-score and Matthew's correlation coefficient.

Authors

  • Zhe Yang
    Department of Pathology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
  • Juan Wang
    Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China.
  • Zhida Zheng
    School of Computer Science, Inner Mongolia University, Hohhot, Inner Mongolia 010021, China. imuzzd@163.com.
  • Xin Bai
    School of Computer Science, Inner Mongolia University, Hohhot, Inner Mongolia 010021, China. 6530071@163.com.