Send to:

Choose Destination
See comment in PubMed Commons below
Biomed Res Int. 2013;2013:686090. doi: 10.1155/2013/686090. Epub 2013 Aug 21.

An approach for identifying cytokines based on a novel ensemble classifier.

Author information

  • 1School of Information Science and Technology, Xiamen University, Xiamen, Fujian, China ; Center for Cloud Computing and Big Data, Xiamen University, Xiamen, Fujian, China ; Shanghai Key Laboratory of Intelligent Information Processing, Shanghai, China.


Biology is meaningful and important to identify cytokines and investigate their various functions and biochemical mechanisms. However, several issues remain, including the large scale of benchmark datasets, serious imbalance of data, and discovery of new gene families. In this paper, we employ the machine learning approach based on a novel ensemble classifier to predict cytokines. We directly selected amino acids sequences as research objects. First, we pretreated the benchmark data accurately. Next, we analyzed the physicochemical properties and distribution of whole amino acids and then extracted a group of 120-dimensional (120D) valid features to represent sequences. Third, in the view of the serious imbalance in benchmark datasets, we utilized a sampling approach based on the synthetic minority oversampling technique algorithm and K-means clustering undersampling algorithm to rebuild the training set. Finally, we built a library for dynamic selection and circulating combination based on clustering (LibD3C) and employed the new training set to realize cytokine classification. Experiments showed that the geometric mean of sensitivity and specificity obtained through our approach is as high as 93.3%, which proves that our approach is effective for identifying cytokines.

[PubMed - indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Hindawi Publishing Corporation Icon for PubMed Central
    Loading ...
    Write to the Help Desk