Protein contact map prediction using committee machine approach
Habibi, N, Saraee, M and Korbekandi, H 2011, 'Protein contact map prediction using committee machine approach' , International Journal of Data Mining and Bioinformatics . (In Press)
|PDF - Published Version |
Restricted to Repository staff only
Download (260kB) | Request a copy
A protein contact map is a simplified representation of the protein's spatial structure. In recent years, contact map prediction has received a great deal of attention in Bioinformatics. Committee Machine is a machine learning method which shares the learning task among 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 paper a novel method called CMP_Model, for contact map prediction based on Committee Machine, is proposed. In this method, the learner group is a set of neural networks. To analyze the results of the proposed model, two other models are implemented and their results are compared and presented. The results show considerable gain (an accuracy improvement from 0.05 to 0.15) which is achievable by the Committee Machine approach in the contact map prediction problem.
|Themes:||Subjects outside of the University Themes|
|Schools:||Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering > Data Mining and Pattern Recognition Research Centre|
|Journal or Publication Title:||International Journal of Data Mining and Bioinformatics|
|Depositing User:||Users 29196 not found.|
|Date Deposited:||21 Dec 2011 15:47|
|Last Modified:||23 Sep 2013 11:17|
Document DownloadsMore statistics for this item...
Actions (login required)
|Edit record (repository staff only)|