Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM
Joint Authors
Xia, Shixiong
Gao, Zhen-Guo
Wang, Lei
You, Zhu-Hong
Yan, Xin
Yong, Zhou
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-06-29
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Protein-Protein Interactions (PPIs) play vital roles in most biological activities.
Although the development of high-throughput biological technologies has generated considerable PPI data for various organisms, many problems are still far from being solved.
A number of computational methods based on machine learning have been developed to facilitate the identification of novel PPIs.
In this study, a novel predictor was designed using the Rotation Forest (RF) algorithm combined with Autocovariance (AC) features extracted from the Position-Specific Scoring Matrix (PSSM).
More specifically, the PSSMs are generated using the information of protein amino acids sequence.
Then, an effective sequence-based features representation, Autocovariance, is employed to extract features from PSSMs.
Finally, the RF model is used as a classifier to distinguish between the interacting and noninteracting protein pairs.
The proposed method achieves promising prediction performance when performed on the PPIs of Yeast, H.
pylori, and independent datasets.
The good results show that the proposed model is suitable for PPIs prediction and could also provide a useful supplementary tool for solving other bioinformatics problems.
American Psychological Association (APA)
Gao, Zhen-Guo& Wang, Lei& Xia, Shixiong& You, Zhu-Hong& Yan, Xin& Yong, Zhou. 2016. Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM. BioMed Research International،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1097810
Modern Language Association (MLA)
Gao, Zhen-Guo…[et al.]. Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM. BioMed Research International No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1097810
American Medical Association (AMA)
Gao, Zhen-Guo& Wang, Lei& Xia, Shixiong& You, Zhu-Hong& Yan, Xin& Yong, Zhou. Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1097810
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1097810