【摘要】 蛋白质二级结构预测是蛋白质功能预测中一个很重要的环节。我们综合考虑了蛋白质序列中对氨基酸二级结构具有影响的因素,采用最大熵模型实现了对蛋白质二级结构的预测。将氨基酸之间的相互作用和氨基酸对于二级结构的倾向性作为特征函数,充分体现了蛋白质序列中氨基酸之间的短程和长程的相互作用的影响。最大熵模型整合了这些多源的信息,形成一个单一的概率模型。与现有的单序列预测方法相比,本文的方法取得了较高的预测准确率,预测结果表明它是一种实用的预测方法。更多还原

【Abstract】 Secondary structure prediction plays an important role in function prediction of protein.In this paper,maximum entropy model is used to predict protein secondary structure.We build feature function sets based on the influential factors which are crucial to the states of secondary structure of residues in protein sequence.Multi-factors are taken into account in the model,including charge of amino acids,conformational parameter for the states of secondary structure, short and long ranges of interaction of residues in sequence.As such,multi-source information is integrated into a single probability model by the method.Compared with the reported methods,our method gets a higher accuracy rate in predicting protein secondary structure.The results demonstrate that the proposed method is practical.更多还原