ArticleMolecules (Basel, Switzerland)2018
A New Method for Recognizing Cytokines Based on Feature Combination and a Support Vector Machine Classifier.
Article in Molecules (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Implementation of PCA enabled Support Vector Machine using cytokines to differentiate smokers versus nonsmokers.Proceedings. International Conference on Computational Science and Computational Intelligence · 2021Article
- TNFPred: identifying tumor necrosis factors using hybrid features based on word embeddings.BMC medical genomics · 2020Article
- Succinylation Site Prediction Based on Protein Sequences Using the IFS-LightGBM (BO) Model.Computational and mathematical methods in medicine · 2020Article
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4 authors.
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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.
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