title: Integrating overlapping structures and background information of words significantly improves biological sequence comparison.
abstract: Word-based models have achieved promising results in sequence comparison. However, as the important statistical properties of words in biological sequence, how to use the overlapping structures and background information of the words to improve sequence comparison is still a problem. This paper proposed a new statistical method that integrates the overlapping structures and the background information of the words in biological sequences. To assess the effectiveness of this integration for sequence comparison, two sets of evaluation experiments were taken to test the proposed model. The first one, performed via receiver operating curve analysis, is the application of proposed method in discrimination between functionally related regulatory sequences and unrelated sequences, intron and exon. The second experiment is to evaluate the performance of the proposed method with f-measure for clustering Hepatitis E virus genotypes. It was demonstrated that the proposed method integrating the overlapping structures and the background information of words significantly improves biological sequence comparison and outperforms the existing models.
authors.affiliation: College of Life Sciences, Zhejiang Sci-Tech University, Hangzhou, People's Republic of China. daiailiu2004@yahoo.com.cn
authors.forename: Qi
authors.initials: Q
authors.lastname: Dai
authors.forename: Lihua
authors.initials: L
authors.lastname: Li
authors.forename: Xiaoqing
authors.initials: X
authors.lastname: Liu
authors.forename: Yuhua
authors.initials: Y
authors.lastname: Yao
authors.forename: Fukun
authors.initials: F
authors.lastname: Zhao
authors.forename: Michael
authors.initials: M
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D005091:Exons / Q000235:genetics; D005838:Genotype; D016752:Hepatitis E virus / Q000235:genetics*; D006801:Humans; D007438:Introns / Q000235:genetics; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D011506:Proteins / Q000235:genetics*; D012372:ROC Curve; D012045:Regulatory Sequences, Nucleic Acid; D016415:Sequence Alignment
chemical_list: D011506:Proteins
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