Vol. 20 no. 1 2004, pages 40-44
Bioinformatics © Oxford University Press 2004; all rights reserved.
Protein ß-turn prediction using nearest-neighbor method
School of Computational Sciences, Korea Institute for Advanced Study, Seoul 130-722, Korea
Received on April 2, 2003
; revised on May 24, 2003
; accepted on July 2, 2003
Motivation: With the emerging success of protein secondary structure prediction through the applications of various statistical and machine learning techniques, similar techniques have been applied to protein ß-turn prediction. In this study, we perform protein ß-turn prediction using a k-nearest neighbor method, which is combined with a filter that uses predicted protein secondary structure information. Traditional ß-turn prediction from k-nearest neighbor method is modified to account for the unbalanced ratio of the natural occurrence of ß-turns and non-ß-turns.
Results: Our prediction scheme is tested on a set of 426 non-homologous protein sequences. The prediction scheme consists of two stages: k-nearest neighbor method stage and filtering stage. Variations of the k-nearest neighbor method were used to take property of ß-turns into consideration. Our filtering method uses ß-turn/non-ß-turn estimates from the k-nearest neighbor method stage and predicted protein secondary structure information from PSI-PRED in order to get new ß-turn/non-ß-turn estimate. Our result is compared with the previously best known ß-turn prediction method on the dataset of 426 non-homologous protein sequences and is shown to give slightly superior performance at significantly lower computational complexity.
Availability: Contact the author for information on the source code of the programs used.
Contact: saejoon{at}kias.re.kr
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