Secondary structure computer prediction of the poiiovirus 5' non-coding region is improved by a genetic algorithm

作     者：Currey, Kathleen M. Shapiro, Bruce A. 

作者机构：SIDS Institute Department of Pediatrics University of Maryland Medical Center Baltimore MD 21201 22 South Greene Street United States Laboratory of Mathematical Biology Division of Basic Sciences National Cancer Institute Frederick Cancer Research and Development Center Frederick MD 21702 United States Image Processing Section Laboratory of Mathematical Biology Division of Basic Sciences National Cancer Institute Frederick Cancer Research and Development Center Frederick MD 21702 United States 

出 版 物：《Bioinformatics》 (Bioinformatics)

年 卷 期：1997年第13卷第1期

页      面：1-12页

学科分类：0710[理学-生物学] 08[工学] 0714[理学-统计学（可授理学、经济学学位）] 0703[理学-化学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

摘      要：Comparison of the secondary structure of the 5 non-coding region of poliovirus 3 RNA derived from the genetic algorithm with the model of Skinner et al. (J. Mol. Biol., 207, 379–392, 1989) demonstrates many of the confirmed structural elements. The genetic algorithm (Shapiro and Navetta, J. Supercomput., 8, 195–201, 1994) generates a population of all possible stems, then mixes, combines, and recombines these stems in multiple iterations on a massively parallel computer, ultimately selecting a most fit structure based on its energy. The secondary structure of the region containing the determinants of neurovirulence was better predicted using the genetic algorithm, whereas the dynamic programing algorithm (Zuker, Science, 244, 48–52, 1989) required phylogenetic comparative sequence analysis to arrive at the correct conclusion. In addition, artificial mutations were introduced throughout this region of the genome and although rearrangements in structure may occur, many structures persisted, suggesting that the given structures thus selected may have evolved to withstand isolated mutations. The genetic algorithm-derived structure for the 5 non-coding region compares favorably with the biological data and functions previously described, and contains all of the ‘persistent’ structures, suggesting also that the persistence factor may be an aid to validating structures. © 1997, Oxford University Press.