Alignment-free sequence analysis

<p>In <a href="/facts/Bioinformatics/D5x2L8ee">bioinformatics</a>, alignment-free sequence analysis approaches to molecular sequence and structure data provide alternatives over alignment-based approaches.
</p><p>The emergence and need for the analysis of different types of data generated through biological research has given rise to the field of <a href="/facts/Bioinformatics/D5x2L8ee">bioinformatics</a>. Molecular sequence and structure data of <a href="/facts/DNA/nB89Iauz">DNA</a>, <a href="/facts/RNA/HxPeNfNj">RNA</a>, and <a href="/facts/Proteins/Jxmagu3E">proteins</a>, <a href="/facts/Gene_expression/alCPohLR">gene expression</a> profiles or <a href="/facts/Microarray/LvJeNodc">microarray</a> data, <a href="/facts/Metabolic_pathway/8Py8HKJd">metabolic pathway</a> data are some of the major types of data being analysed in bioinformatics. Among them sequence data is increasing at the exponential rate due to advent of next-generation sequencing technologies. Since the origin of bioinformatics, <a href="/facts/Sequence_analysis/QJvMmLg9">sequence analysis</a> has remained the major area of research with wide range of applications in database searching, <a href="/facts/Genome_annotation/HY6IuzMT">genome annotation</a>, <a href="/facts/Comparative_genomics/fKMXJS7f">comparative genomics</a>, <a href="/facts/Molecular_phylogeny/FysplHP5">molecular phylogeny</a> and <a href="/facts/Gene_prediction/QFdMeIN2">gene prediction</a>. The pioneering approaches for sequence analysis were based on <a href="/facts/Sequence_alignment/p8GQfF7b">sequence alignment</a> either global or local, pairwise or <a href="/facts/Multiple_sequence_alignment/en7c7SQs">multiple sequence alignment</a>. Alignment-based approaches generally give excellent results when the sequences under study are closely related and can be reliably aligned, but when the sequences are divergent, a reliable alignment cannot be obtained and hence the applications of sequence alignment are limited. Another limitation of alignment-based approaches is their computational complexity and are time-consuming and thus, are limited when dealing with large-scale sequence data. The advent of <a href="/facts/Next-generation_sequencing/FjLl8GGa">next-generation sequencing</a> technologies has resulted in generation of voluminous sequencing data. The size of this sequence data poses challenges on alignment-based algorithms in their assembly, annotation and comparative studies.
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Alignment-free sequence analysis open-in-new

Alignment-free sequence analysis