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Real Protein Prediction in an Off-Lattice BLN Model via Annealing Contour Monte Carlo
Real Protein Prediction in an Off-Lattice BLN Model via Annealing Contour Monte Carlo
초록
Recently, the general contour Monte Carlo has been proposed by Liang (2004) as a space annealing version(ACMC) for optimization problems. The algorithm can be applied successfully to determine the ground configurations for the prediction of protein folding. In this approach, we use the distances between the consecutive $C_alpha atoms along the peptide chain and the mapping sequences between the 20-letter amino acids and a coarse-grained three-letter code. The algorithm was tested on the real proteins. The comparison showed that the algorithm made a significant improvement over the simulated annealing(SA) and the Metropolis Monte Carlo method in determining the ground configurations.
키워드
Protein folding; annealing contour Monte Carlo; simulated annealing; BLN model.
- 제목
- Real Protein Prediction in an Off-Lattice BLN Model via Annealing Contour Monte Carlo
- 제목 (타언어)
- Real Protein Prediction in an Off-Lattice BLN Model via Annealing Contour Monte Carlo
- 저자
- 전수영
- 발행일
- 2009
- 저널명
- 응용통계연구
- 권
- 22
- 호
- 3
- 페이지
- 627 ~ 634
- 언어
- ENG
- 출판사
- 한국통계학회
- 발행국가
- 대한민국
- 분량
- 8 페이지
- ISSN
- P 1225-066X