A Gram-Negative Bacterial Secreted Protein Types Prediction Method Based on PSI-BLAST Profile
Joint Authors
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-08-02
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Abstract EN
Prediction of secreted protein types based solely on sequence data remains to be a challenging problem.
In this study, we extract the long-range correlation information and linear correlation information from position-specific score matrix (PSSM).
A total of 6800 features are extracted at 17 different gaps; then, 309 features are selected by a filter feature selection method based on the training set.
To verify the performance of our method, jackknife and independent dataset tests are performed on the test set and the reported overall accuracies are 93.60% and 100%, respectively.
Comparison of our results with the existing method shows that our method provides the favorable performance for secreted protein type prediction.
American Psychological Association (APA)
Ding, Shuyan& Zhang, Shengli. 2016. A Gram-Negative Bacterial Secreted Protein Types Prediction Method Based on PSI-BLAST Profile. BioMed Research International،Vol. 2016, no. 2016, pp.1-5.
https://search.emarefa.net/detail/BIM-1097302
Modern Language Association (MLA)
Ding, Shuyan& Zhang, Shengli. A Gram-Negative Bacterial Secreted Protein Types Prediction Method Based on PSI-BLAST Profile. BioMed Research International No. 2016 (2016), pp.1-5.
https://search.emarefa.net/detail/BIM-1097302
American Medical Association (AMA)
Ding, Shuyan& Zhang, Shengli. A Gram-Negative Bacterial Secreted Protein Types Prediction Method Based on PSI-BLAST Profile. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-5.
https://search.emarefa.net/detail/BIM-1097302
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1097302