Name
Title | ||
|---|---|---|
A new representation for protein secondary structure prediction based on frequent patterns. |
Abstract | ||
|---|---|---|
A new representation for protein secondary structure prediction based on frequent amino acid patterns is described and evaluated. We discuss in detail how to identify frequent patterns in a protein sequence database using a level-wise search technique, how to define a set of features from those patterns and how to use those features in the prediction of the secondary structure of a protein sequence using support vector machines (SVMs).Three different sets of features based on frequent patterns are evaluated in a blind testing setup using 150 targets from the EVA contest and compared to predictions of PSI-PRED, PHD and PROFsec. Despite being trained on only 940 proteins, a simple SVM classifier based on this new representation yields results comparable to PSI-PRED and PROFsec. Finally, we show that the method contributes significant information to consensus predictions.The method is available from the authors upon request. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1093/bioinformatics/btl453 | Bioinformatics |
Keywords | Field | DocType |
protein secondary structure prediction,protein sequence database,frequent amino acid pattern,eva contest,new representation,secondary structure,frequent pattern,consensus prediction,new representation yields result,protein sequence,amino acid,difference set,support vector machine | Protein secondary structure prediction,Data mining,Sequence database,Protein sequencing,Pattern recognition,Computer science,Support vector machine,Artificial intelligence,Bioinformatics,Svm classifier,Protein secondary structure | Journal |
Volume | Issue | ISSN |
22 | 21 | 1367-4811 |
Citations | PageRank | References |
21 | 1.37 | 9 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fabian Birzele | 1 | 74 | 5.52 |
| Stefan Kramer | 2 | 1313 | 141.90 |