基于最大频繁序列的蛋白质分类算法

针对现有基于频繁模式的分类算法未考虑完全频繁模式所产生的大量无效序列,提出了一种基于最大频繁序列的蛋白质分类算法,此算法每一类都以独有的最大频繁模式作为代表,执行模式裁减和测试数据分类。实验表明该算法在继承传统算法优点的同时提高了结果的精确度,降低了模式的冗余度,此应用增加了分类的生物信息学意义。

Protein Sequence Classification Algorithm Based on Maximal Frequent Sequence

Aimed at the massive invalid sequences caused by the complete frequent patterns,which is not con- sidered in the existing classification algorithm,a protein sequence classification algorithm is proposed based on the maximal frequent sequence.In this algorithm each class can be presented by the particular maximal frequent pattern,then the pattern can be reduced and the test data can be classified.Experiments show that this algorithm can improve the precision of results and reduce the redundancy of the pattern with remaining the advantages of the traditional algorithm,the bioinformatics meaning can then be increased through such an application.