CAJ | 학술논문

[目的]研究基于词条提取云模型预测RNA二级结构的方法。[方法]将云模型引入到随机文法模型中，提出适合于词汇化随机文法模型的机器学习算法，通过词网格模型对RNA序列进行词条获取和划分，再经过云分类器搜索每个词条被标注为某种二级结构类型的最大概率，然后将这些词条信息作为先验信息在随机文法云模型训练过程中引入，实现对RNA二级结构的预测，并对该方法进行试验检测。[结果]试验测试表明，在随机文法模型中引入云模型后，其在预测的准确度和搜索速度上较单纯的随机文法效果有明显改善。[结论]该研究为随机文法模型在RNA二级结构预测中的广泛应用奠定了基础。
[목적]연구기우사조제취운모형예측RNA이급결구적방법。[방법]장운모형인입도수궤문법모형중，제출괄합우사회화수궤문법모형적궤기학습산법，통과사망격모형대RNA서렬진행사조획취화화분，재경과운분류기수색매개사조피표주위모충이급결구류형적최대개솔，연후장저사사조신식작위선험신식재수궤문법운모형훈련과정중인입，실현대RNA이급결구적예측，병대해방법진행시험검측。[결과]시험측시표명，재수궤문법모형중인입운모형후，기재예측적준학도화수색속도상교단순적수궤문법효과유명현개선。[결론]해연구위수궤문법모형재RNA이급결구예측중적엄범응용전정료기출。
[Objective] To examine the grammar model based on lexical substring exac- tion for RNA secondary structure prediction. [Method] By introducing cloud model into stochastic grammar model, a machine learning algorithm suitable for the lexicalized stochastic grammar model was proposed. The word grid mode was used to extract and divide RNA sequence to acquire lexical substring, and the cloud classifier was used to search the maximum probability of each lemma which was marked as a certain sec- ondary structure type. Then, the lemma information was introduced into the training stochastic grammar process as prior information, realizing the prediction on the sec- ondary structure of RNA, and the method was tested by experiment. [Result] The experimental results showed that the prediction accuracy and searching speed of stochastic grammar cloud model were significantly improved from the prediction with simple stochastic grammar. [Conclusion] This study laid the foundation for the wide application of stochastic grammar model for RNA secondary structure prediction.