Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Ensemble of Probabilistic Neural Networks for Protein Fold Recognition

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
4 Author(s)

Protein data contain discriminative patterns that can be used in many beneficial applications if they are defined correctly. Protein classification in terms of fold recognition plays an important role in computational protein analysis, since it can contribute to the determination of the function of a protein whose structure is unknown. In this paper, a probabilistic neural network ensemble (PNNE) model is proposed for multi-class protein folds recognition problem. For training and evaluating the proposed method we use two datasets containing 27 SCOP folds. Experimental results show that the proposed method can improve the prediction accuracy and outperform other related approaches.

Published in:

Bioinformatics and Bioengineering, 2007. BIBE 2007. Proceedings of the 7th IEEE International Conference on

Date of Conference:

14-17 Oct. 2007