A New Method for Recognizing Cytokines Based on Feature Combination and a Support Vector Machine Classifier
- PMID: 30103521
- PMCID: PMC6222536
- DOI: 10.3390/molecules23082008
A New Method for Recognizing Cytokines Based on Feature Combination and a Support Vector Machine Classifier
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.
Keywords: PSSM; PseAAC; SVM; cytokines; feature combination.
Conflict of interest statement
The authors declare no conflict of interest.
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