Pattern recognition and probabilistic measures in alignment-free sequence analysis
نویسندگان
چکیده
منابع مشابه
Pattern recognition and probabilistic measures in alignment-free sequence analysis
With the massive production of genomic and proteomic data, the number of available biological sequences in databases has reached a level that is not feasible anymore for exact alignments even when just a fraction of all sequences is used. To overcome this inevitable time complexity, ultrafast alignment-free methods are studied. Within the past two decades, a broad variety of nonalignment method...
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MOTIVATION Alignment-based sequence similarity searches, while accurate for some type of sequences, can produce incorrect results when used on more divergent but functionally related sequences that have undergone the sequence rearrangements observed in many bacterial and viral genomes. Here, we propose a classification model that exploits the complementary nature of alignment-based and alignmen...
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Genome and metagenome comparisons based on large amounts of next generation sequencing (NGS) data pose significant challenges for alignment-based approaches due to the huge data size and the relatively short length of the reads. Alignment-free approaches based on the counts of word patterns in NGS data do not depend on the complete genome and are generally computationally efficient. Thus, they ...
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We describe an new algorithm for visualizing an alignment of biological sequences according to a probabilistic model of evolution. The resulting data array is readily interpreted by the human eye and amenable to digital image techniques. We present examples using mRNA sequences from mouse and rat: three cytochromes and two zinc finger proteins. The underlying evolutionary model is derived from ...
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MOTIVATION Alignment-free sequence comparison methods are still in the early stages of development compared to those of alignment-based sequence analysis. In this paper, we introduce a probabilistic measure of similarity between two biological sequences without alignment. The method is based on the concept of comparing the similarity/dissimilarity between two constructed Markov models. RESULT...
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ژورنال
عنوان ژورنال: Briefings in Bioinformatics
سال: 2013
ISSN: 1467-5463,1477-4054
DOI: 10.1093/bib/bbt070