JPPRED: Prediction of Types of J-Proteins from Imbalanced Data Using an Ensemble Learning Method
Joint Authors
Zhang, Chengjin
Zhang, Lina
Gao, Rui
Yang, Runtao
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-26
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Different types of J-proteins perform distinct functions in chaperone processes and diseases development.
Accurate identification of types of J-proteins will provide significant clues to reveal the mechanism of J-proteins and contribute to developing drugs for diseases.
In this study, an ensemble predictor called JPPRED for J-protein prediction is proposed with hybrid features, including split amino acid composition (SAAC), pseudo amino acid composition (PseAAC), and position specific scoring matrix (PSSM).
To deal with the imbalanced benchmark dataset, the synthetic minority oversampling technique (SMOTE) and undersampling technique are applied.
The average sensitivity of JPPRED based on above-mentioned individual feature spaces lies in the range of 0.744–0.851, indicating the discriminative power of these features.
In addition, JPPRED yields the highest average sensitivity of 0.875 using the hybrid feature spaces of SAAC, PseAAC, and PSSM.
Compared to individual base classifiers, JPPRED obtains more balanced and better performance for each type of J-proteins.
To evaluate the prediction performance objectively, JPPRED is compared with previous study.
Encouragingly, JPPRED obtains balanced performance for each type of J-proteins, which is significantly superior to that of the existing method.
It is anticipated that JPPRED can be a potential candidate for J-protein prediction.
American Psychological Association (APA)
Zhang, Lina& Zhang, Chengjin& Gao, Rui& Yang, Runtao. 2015. JPPRED: Prediction of Types of J-Proteins from Imbalanced Data Using an Ensemble Learning Method. BioMed Research International،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1056437
Modern Language Association (MLA)
Zhang, Lina…[et al.]. JPPRED: Prediction of Types of J-Proteins from Imbalanced Data Using an Ensemble Learning Method. BioMed Research International No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1056437
American Medical Association (AMA)
Zhang, Lina& Zhang, Chengjin& Gao, Rui& Yang, Runtao. JPPRED: Prediction of Types of J-Proteins from Imbalanced Data Using an Ensemble Learning Method. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1056437
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1056437