Title
PPM-Dom
Abstract
PPM-Dom could predict the exact positions of each domain in any query proteins.PPM-Dom could distinguish different domains in the same query sequence from each other.PPM-Dom could figure out each part of the discontinuous domain regions.The number of domains would be inferred effortlessly from the positions of domains. Domains are the structural basis of the physiological functions of proteins, and the prediction of which is an advantageous process on the study of protein structure and function. This article proposes a new complete automatic prediction method, PPM-Dom (Domain Position Prediction Method), for predicting the particular positions of domains in a target protein via its atomic coordinate. The presented method integrates complex networks, community division, and fuzzy mean operator (FMO). The whole sequences are divided into potential domain regions by the complex network and community division, and FMO allows the final determination for the domain position. This method will suffice to predict regions that will form a domain structure and those that are unstructured based on completely new atomic coordinate information of the query sequence, and be able to separate different domains in the same query sequence from each other. On evaluating the performance using an independent testing dataset, PPM-Dom reached 91.41% for prediction accuracy, 96.12% for sensitivity and 92.86% for specificity. The tool bag of PPM-Dom is freely available at http://cic.scu.edu.cn/bioinformatics/PPMDom.zip.
Year
DOI
Venue
2013
10.1016/j.compbiolchem.2013.06.002
Computational Biology and Chemistry
Keywords
Field
DocType
community division,domain position prediction,prediction accuracy,novel method,domain position,complex network,potential domain region,new complete automatic prediction,fuzzy mean operator,protein structure,query sequence,different domain,domain structure
Computer science,Fuzzy logic,Operator (computer programming),Complex network,Bioinformatics,Protein structure
Journal
Volume
Issue
ISSN
47
C
1476-928X
Citations 
PageRank 
References 
2
0.39
31
Authors
6
Name
Order
Citations
PageRank
Jing Sun120.39
Runyu Jing231.42
Yue-Long Wang321.41
Tuanfei Zhu430.74
Menglong Li59411.85
Yizhou Li6694.70