SPADE: an efficient algorithm for mining frequent sequences
Machine Learning
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Enumerating and Ranking Discrete Motifs
Proceedings of the 5th International Conference on Intelligent Systems for Molecular Biology
Scalable sequential pattern mining for biological sequences
Proceedings of the thirteenth ACM international conference on Information and knowledge management
An Evaluation of Approaches to Classification Rule Selection
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
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The prediction of protein sequence function is one of the problems arising in the recent progress in bioinformatics. Traditional methods have its limits. We present a novel method of protein sequence function prediction based on sequential pattern mining. First, we use our designed sequential pattern mining algorithms to mine known function sequence dataset. Then, we build a classifier using the patterns generated to predict function of protein sequences. Experiments confirm the effectiveness of our method.