Protein contact map prediction using committee machine approach. (1st January 2013)

• Record Type: Journal Article
• Authors: Habibi, Narjeskhatoon; Saraee, Mohamad; Korbekandi, Hassan
• Is Part Of: International journal of data mining and bioinformatics. Volume 7:Number 4(2013)
• Page Start: 397
• Page End: 415
• Publication Date: 2013-01-01
• Subjects: bioinformatics -- artificial intelligence -- machine learning -- committee machine -- ensemble learning -- data mining -- neural network -- protein contact map -- contact map prediction; Data mining -- Periodicals; Bioinformatics -- Periodicals; 006.312
• Languages: English
• ISSNs: 1748-5673

Abstract

Protein contact map is a simplified representation of a protein's spatial structure. The Committee Machine is a machine learning method that allots the learning task to a number of learners and divides the input space into subspaces. Learners' responses to an input are combined to produce the system's final response, which is more accurate than any single individual's response. In this study, we propose a novel method called CMP_model, for contact map prediction based on the committee machine. The results of the proposed model in comparison with two other models, show considerable gain (an accuracy improvement from 0.05 to 0.15).