On the significance of sequence alignments when using multiple scoring matrices

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On the significance of sequence alignments when using multiple scoring matrices

MOTIVATION Pairwise local sequence alignment is commonly used to search data bases for sequences related to some query sequence. Alignments are obtained using a scoring matrix that takes into account the different frequencies of occurrence of the various types of amino acid substitutions. Software like BLAST provides the user with a set of scoring matrices available to choose from, and in the l...

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Global Pairwise Sequence Alignments with Multiple Scoring Matrices

A necessity of repeating alignments on a same pair of sequences to select an appropriate scoring function to detect a significance of score motivates us to work on higher performance matching technique. While overlapping each alignments obtained through a set of typical scoring matrix with its default gap cost, we observe significant parameters that may induce a maximum deviation from a referen...

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Finding Winner Alignments with Multiple Scoring Matrices

How to align two given sequences properly is a fundamental problem in bioinformatics. In the sequence alignment problem, the most essential thing that directly affects the resulting alignment is the scoring matrix. There are a variety of scoring matrices used for alignment, and each of them has its own purpose in biosequence alignment. It seems unlikely that an alignment is optimal for each sco...

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Scoring Pairwise Genomic Sequence Alignments

The parameters by which alignments are scored can strongly affect sensitivity and specificity of alignment procedures. While appropriate parameter choices are well understood for protein alignments, much less is known for genomic DNA sequences. We describe a straightforward approach to scoring nucleotide substitutions in genomic sequence alignments, especially human-mouse comparisons. Scores ar...

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Adjusting scoring matrices to correct overextended alignments

MOTIVATION Sequence similarity searches performed with BLAST, SSEARCH and FASTA achieve high sensitivity by using scoring matrices (e.g. BLOSUM62) that target low identity (<33%) alignments. Although such scoring matrices can effectively identify distant homologs, they can also produce local alignments that extend beyond the homologous regions. RESULTS We measured local alignment start/stop b...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2004

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/btg498