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Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences
Joint Authors
You, Zhu-Hong
An, Ji-Yong
Fang, Yu-Hong
Zhao, Yu-Jun
Zhang, Ming
Fanrong, Meng
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-05-23
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
We propose a novel computational method known as RVM-LPQ that combines the Relevance Vector Machine (RVM) model and Local Phase Quantization (LPQ) to predict PPIs from protein sequences.
The main improvements are the results of representing protein sequences using the LPQ feature representation on a Position Specific Scoring Matrix (PSSM), reducing the influence of noise using a Principal Component Analysis (PCA), and using a Relevance Vector Machine (RVM) based classifier.
We perform 5-fold cross-validation experiments on Yeast and Human datasets, and we achieve very high accuracies of 92.65% and 97.62%, respectively, which is significantly better than previous works.
To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the Yeast dataset.
The experimental results demonstrate that our RVM-LPQ method is obviously better than the SVM-based method.
The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool for future proteomics research.
American Psychological Association (APA)
An, Ji-Yong& Fanrong, Meng& You, Zhu-Hong& Fang, Yu-Hong& Zhao, Yu-Jun& Zhang, Ming. 2016. Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences. BioMed Research International،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1097890
Modern Language Association (MLA)
An, Ji-Yong…[et al.]. Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences. BioMed Research International No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1097890
American Medical Association (AMA)
An, Ji-Yong& Fanrong, Meng& You, Zhu-Hong& Fang, Yu-Hong& Zhao, Yu-Jun& Zhang, Ming. Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1097890
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1097890