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pmid: 11084899
Publisher Summary This chapter discusses various aspects of multiple sequence alignment. Dynamic programming can be generalized to more than two sequences where one finds the multiple alignments with the best score according to the scoring scheme. Gaps are scored according to their length and the number of sequences that they occur in and the method will find a multiple alignment with the best possible score. Clustal W is perhaps the most widely used program for carrying out automatic multiple alignments. It uses a simple text menu system or command-line interface that is reasonably self-explanatory and simple to use. It allows one to carry out fully automatic and rapid alignments of dozens of sequences of moderate length using the progressive alignment method. The main menu leads to submenus for calculating phylogenetic trees from multiple alignments and for the alignment of existing alignments. The trees cannot be displayed by Clustal W but can be viewed using dedicated tree-viewing programs. The alignments that are produced by Clustal W and X are sent to simple text files. These show the sequences aligned in blocks and use symbols to indicate residues that are exactly conserved in columns or which show some degree of biochemical conservation in the columns. It is found that dedicated alignment editors can move large gaps quickly and can be persuaded to color the columns of residues depending on the degree of conservation and/or residue type.
Protein Folding, Protein Conformation, Amino Acid Motifs, Molecular Sequence Data, Flavodoxin, Proteins, Protein Structure, Secondary, Amino Acid Sequence, Sequence Alignment, Algorithms, Phylogeny, Software
Protein Folding, Protein Conformation, Amino Acid Motifs, Molecular Sequence Data, Flavodoxin, Proteins, Protein Structure, Secondary, Amino Acid Sequence, Sequence Alignment, Algorithms, Phylogeny, Software
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 31 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |