Characterizing the D2 Statistic: Word Matches in Biological Sequences
暂无分享,去创建一个
[1] Takuji Nishimura,et al. Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator , 1998, TOMC.
[2] Andrew D. Barbour,et al. Compound Poisson approximation: a user's guide , 2001 .
[3] Sylvain Forêt,et al. Empirical distribution of k , 2009, Pattern Recognit..
[4] D. Davison,et al. d2_cluster: a validated method for clustering EST and full-length cDNAsequences. , 1999, Genome research.
[5] M S Waterman,et al. Identification of common molecular subsequences. , 1981, Journal of molecular biology.
[6] Zsuzsanna Lipták,et al. An overview of the wcd EST clustering tool , 2008, Bioinform..
[7] Susan R. Wilson,et al. Approximate word matches between two random sequences , 2008 .
[8] M. F. Fuller,et al. Practical Nonparametric Statistics; Nonparametric Statistical Inference , 1973 .
[9] Sylvain Forêt,et al. Asymptotic behaviour and optimal word size for exact and approximate word matches between random sequences , 2006, BMC Bioinformatics.
[10] Jonas S. Almeida,et al. Alignment-free sequence comparison-a review , 2003, Bioinform..
[11] M. Waterman,et al. Distributional regimes for the number of k-word matches between two random sequences , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[12] Winston Hide,et al. Biological Evaluation of d2, an Algorithm for High-Performance Sequence Comparison , 1994, J. Comput. Biol..
[13] Saurabh Sinha,et al. A statistical method for alignment-free comparison of regulatory sequences , 2007, ISMB/ECCB.
[14] Robert Miller,et al. STACK: Sequence Tag Alignment and Consensus Knowledgebase , 2001, Nucleic Acids Res..
[15] John E. Carpenter,et al. Assessment of the parallelization approach of d2_cluster for high‐performance sequence clustering , 2002, J. Comput. Chem..
[16] W. J. Kent,et al. BLAT--the BLAST-like alignment tool. , 2002, Genome research.
[17] M. Kimura. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences , 1980, Journal of Molecular Evolution.
[18] Arcady R. Mushegian,et al. Distribution of words with a predefined range of mismatches to a DNA probe in bacterial genomes , 2004, Bioinform..
[19] M. Ragan,et al. Is Multiple-Sequence Alignment Required for Accurate Inference of Phylogeny? , 2007, Systematic biology.
[20] E. J. Gumbel,et al. Statistics of Extremes. , 1960 .
[21] W. Pearson. Rapid and sensitive sequence comparison with FASTP and FASTA. , 1990, Methods in enzymology.
[22] Christoforos Nikolaou,et al. “Word” Preference in the Genomic Text and Genome Evolution: Different Modes of n-tuplet Usage in Coding and Noncoding Sequences , 2005, Journal of Molecular Evolution.
[23] Tiee-Jian Wu,et al. Optimal word sizes for dissimilarity measures and estimation of the degree of dissimilarity between DNA sequences , 2005, Bioinform..
[24] Craig A. Stewart,et al. Introduction to computational biology , 2005 .
[25] C. J. Burden,et al. Asymptotic Behavior of k-Word Matches Between two Uniformly Distributed Sequences , 2007, Journal of Applied Probability.
[26] G. Rubin,et al. A computer program for aligning a cDNA sequence with a genomic DNA sequence. , 1998, Genome research.
[27] Lukas Wagner,et al. A Greedy Algorithm for Aligning DNA Sequences , 2000, J. Comput. Biol..