rna secondary structure alignment has received more attention since the discovery of the structure-function relationships in some non-protein-encoding rnas. However, unlike the pure sequence alignment problem, which h...
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rna secondary structure alignment has received more attention since the discovery of the structure-function relationships in some non-protein-encoding rnas. However, unlike the pure sequence alignment problem, which has been solved in polynomial time, secondarystructurealignment incorporates the base pairings as another information dimension in addition to the base sequence. This problem therefore becomes more challenging. In this study, we classify the selected approaches, and algorithmically illustrate how these methods address the alignment problems with different structure types. Other features such as the types of base pair edit operations supported and the time complexity are also compared.
Recent studies underscore the significant role of rnasecondarystructures in various biological and pathological processes. Structural conservation can reveal homologies undetectable by sequence analysis alone, makin...
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Background The functions of rna molecules are mainly determined by their secondarystructures. These functions can also be predicted using bioinformatic tools that enable the alignment of multiple rnas to determine fu...
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Background The functions of rna molecules are mainly determined by their secondarystructures. These functions can also be predicted using bioinformatic tools that enable the alignment of multiple rnas to determine functional domains and/or classify rna molecules into rna families. However, the existing multiple rnaalignment tools, which use structural information, are slow in aligning long molecules and/or a large number of molecules. Therefore, a more rapid tool for multiple rnaalignment may improve the classification of known rnas and help to reveal the functions of newly discovered rnas. Results Here, we introduce an extremely fast Python-based tool called rnalign2D. It converts rna sequences to pseudo-amino acid sequences, which incorporate structural information, and uses a customizable scoring matrix to align these rna molecules via the multiple protein sequence alignment tool MUSCLE. Conclusions rnalign2D produces accurate rnaalignments in a very short time. The pseudo-amino acid substitution matrix approach utilized in rnalign2D is applicable for virtually all protein aligners.
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