Next Article in Journal
Synthesis and Antimicrobial Studies of Some Novel Bis-[1,3,4]thiadiazole and Bis-thiazole Pendant to Thieno[2,3-b]thiophene Moiety
Previous Article in Journal
Optimization of Serine Protease Purification from Mango (Mangifera indica cv. Chokanan) Peel in Polyethylene Glycol/Dextran Aqueous Two Phase System
Int. J. Mol. Sci. 2012, 13(3), 3650-3660; doi:10.3390/ijms13033650
Article

Prediction of Bioluminescent Proteins Using Auto Covariance Transformation of Evolutional Profiles

1,2
,
1
,
3,* , 2,*  and 1,*
Received: 10 January 2012 / Revised: 21 February 2012 / Accepted: 5 March 2012 / Published: 19 March 2012
View Full-Text   |   Download PDF [181 KB, uploaded 19 June 2014]   |   Browse Figures

Abstract

Bioluminescent proteins are important for various cellular processes, such as gene expression analysis, drug discovery, bioluminescent imaging, toxicity determination, and DNA sequencing studies. Hence, the correct identification of bioluminescent proteins is of great importance both for helping genome annotation and providing a supplementary role to experimental research to obtain insight into bioluminescent proteins’ functions. However, few computational methods are available for identifying bioluminescent proteins. Therefore, in this paper we develop a new method to predict bioluminescent proteins using a model based on position specific scoring matrix and auto covariance. Tested by 10-fold cross-validation and independent test, the accuracy of the proposed model reaches 85.17% for the training dataset and 90.71% for the testing dataset respectively. These results indicate that our predictor is a useful tool to predict bioluminescent proteins. This is the first study in which evolutionary information and local sequence environment information have been successfully integrated for predicting bioluminescent proteins. A web server (BLPre) that implements the proposed predictor is freely available.
Keywords: bioluminescent proteins; position specific scoring matrix; support vector machine; evolutionary information bioluminescent proteins; position specific scoring matrix; support vector machine; evolutionary information
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
EndNote
MDPI and ACS Style

Zhao, X.; Li, J.; Huang, Y.; Ma, Z.; Yin, M. Prediction of Bioluminescent Proteins Using Auto Covariance Transformation of Evolutional Profiles. Int. J. Mol. Sci. 2012, 13, 3650-3660.

View more citation formats

Related Articles

Article Metrics

Comments

Citing Articles

[Return to top]
Int. J. Mol. Sci. EISSN 1422-0067 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert