MAGUS: Multiple sequence Alignment using Graph clUStering
نویسندگان
چکیده
منابع مشابه
Clustering Traces Using Sequence Alignment
Process mining discovers process models from even logs. Logs containing heterogeneous sets of traces can lead to complex process models that try to account for very different behaviour in a single model. Trace clustering identifies homogeneous sets of traces within a heterogeneous log and allows for the discovery of multiple, simpler process models. In this paper, we present a trace clustering ...
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An algorithm is presented for the multiple alignment of sequences, either proteins or nucleic acids, that is both accurate and easy to use on microcomputers. The approach is based on the conventional dynamic-programming method of pairwise alignment. Initially, a hierarchical clustering of the sequences is performed using the matrix of the pairwise alignment scores. The closest sequences are ali...
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Sequence alignment is an important task in bioinformatics which involves typical database search where data is in the form of DNA, RNA or protein sequence. For alignment various methods have been devised starting from pairwise alignment to multiple sequence alignment (MSA). To perform multiple sequence alignment various methods exists like progressive, iterative and concepts of dynamic programm...
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Motivation: An apparent paradox in computational RNA structure prediction is that many methods, in advance, require a multiple alignment of a set of related sequences, when searching for a common structure between them. However, such a multiple alignment is hard to obtain even for few sequences with low sequence similarity without simultaneously folding and aligning them. Furthermore, it is of ...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 2020
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/btaa992