RNA二级结构预测算法的研究进展

在简要介绍了RNA的基础知识之后,对RNA二级结构的定义、表示方法、数据库等内容进行了详细阐述,并重点探讨了RNA二级结构预测方法的原理、适用范围及优缺点.目前,传统的RNA二级结构预测方法有比较序列分析法和最小自由能算法;新进发展的算法有支持向量机算法、基于堆积协变信息与最小自由能算法、基于局部茎搜索的算法、基于快速动态权重匹配算法、免疫粒子群算法、基于茎区的自由能算法、质心法.经过预测精度、复杂度、预测假节能力的对比,发现基于堆积协变信息与最小自由能算法和基于快速动态权重匹配算法,预测结果比较理想.

Review of RNA Secondary Structure Prediction Algorithms

With RNA was found to have important biological functions, RNA research has gradually become a hotspot. Phylogenetic Methods and Minimum Free Energy algorithm has been widely used to predict RNA secondary structure, because of the limitations of the two algorithms, there has emerged many new algorithms .This paper gives a review of the current research progress about RNA secondary structure, including the RNA secondary structure, representing methods of RNA secondary structure, databases of RNA secondary structure, the traditionally and recently new developed RNA prediction algorithms as well as the advantages and disadvantages of the said algorithms. Support Vector Mechanism, Covariance with Stacking and Minimum Free Energy, StemFind, Fast Searching of Max Dynamic Weight Stem, algorithm based on immune partial swarm optimization ensemble, algorithm-helix-based dynamic programming and Centroid are mainly introduced in this paper. After comparison of precision, complexity and capability of predicting knots, Covariance with Stacking based on Minimum Free Energy and Fast Searching of Max Dynamic Weight Stem are ideal combination algorithms.