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Recognition of 27-Class Protein Folds by Adding the Interaction of Segments and Motif Information
Joint Authors
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-20
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
The recognition of protein folds is an important step for the prediction of protein structure and function.
After the recognition of 27-class protein folds in 2001 by Ding and Dubchak, prediction algorithms, prediction parameters, and new datasets for the prediction of protein folds have been improved.
However, the influences of interactions from predicted secondary structure segments and motif information on protein folding have not been considered.
Therefore, the recognition of 27-class protein folds with the interaction of segments and motif information is very important.
Based on the 27-class folds dataset built by Liu et al., amino acid composition, the interactions of secondary structure segments, motif frequency, and predicted secondary structure information were extracted.
Using the Random Forest algorithm and the ensemble classification strategy, 27-class protein folds and corresponding structural classification were identified by independent test.
The overall accuracy of the testing set and structural classification measured up to 78.38% and 92.55%, respectively.
When the training set and testing set were combined, the overall accuracy by 5-fold cross validation was 81.16%.
In order to compare with the results of previous researchers, the method above was tested on Ding and Dubchak’s dataset which has been widely used by many previous researchers, and an improved overall accuracy 70.24% was obtained.
American Psychological Association (APA)
Feng, Zhenxing& Hu, Xiuzhen. 2014. Recognition of 27-Class Protein Folds by Adding the Interaction of Segments and Motif Information. BioMed Research International،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-458491
Modern Language Association (MLA)
Feng, Zhenxing& Hu, Xiuzhen. Recognition of 27-Class Protein Folds by Adding the Interaction of Segments and Motif Information. BioMed Research International No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-458491
American Medical Association (AMA)
Feng, Zhenxing& Hu, Xiuzhen. Recognition of 27-Class Protein Folds by Adding the Interaction of Segments and Motif Information. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-458491
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-458491