title: An efficient binomial model-based measure for sequence comparison and its application.
abstract: Sequence comparison is one of the major tasks in bioinformatics, which could serve as evidence of structural and functional conservation, as well as of evolutionary relations. There are several similarity/dissimilarity measures for sequence comparison, but challenges remains. This paper presented a binomial model-based measure to analyze biological sequences. With help of a random indicator, the occurrence of a word at any position of sequence can be regarded as a random Bernoulli variable, and the distribution of a sum of the word occurrence is well known to be a binomial one. By using a recursive formula, we computed the binomial probability of the word count and proposed a binomial model-based measure based on the relative entropy. The proposed measure was tested by extensive experiments including classification of HEV genotypes and phylogenetic analysis, and further compared with alignment-based and alignment-free measures. The results demonstrate that the proposed measure based on binomial model is more efficient.
authors.affiliation: School of Science, Hangzhou Dianzi Unviersity, Hangzhou 310018, People's Republic of China.
authors.forename: Xiaoqing
authors.initials: X
authors.lastname: Liu
authors.forename: Qi
authors.initials: Q
authors.lastname: Dai
authors.forename: Lihua
authors.initials: L
authors.lastname: Li
authors.forename: Zerong
authors.initials: Z
authors.lastname: He
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D005838:Genotype; D016752:Hepatitis E virus / Q000145:classification / Q000235:genetics; D006801:Humans; D015233:Models, Statistical; D010802:Phylogeny; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA