Abstract | ||
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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 |
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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 Sun | 1 | 2 | 0.39 |
Runyu Jing | 2 | 3 | 1.42 |
Yue-Long Wang | 3 | 2 | 1.41 |
Tuanfei Zhu | 4 | 3 | 0.74 |
Menglong Li | 5 | 94 | 11.85 |
Yizhou Li | 6 | 69 | 4.70 |