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Quality assessment of multiple alignment programs
Author(s) -
Lassmann Timo,
Sonnhammer Erik L.L
Publication year - 2002
Publication title -
febs letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.593
H-Index - 257
eISSN - 1873-3468
pISSN - 0014-5793
DOI - 10.1016/s0014-5793(02)03189-7
Subject(s) - multiple sequence alignment , alignment free sequence analysis , sequence (biology) , sequence alignment , similarity (geometry) , computer science , structural alignment , contrast (vision) , computational biology , artificial intelligence , algorithm , pattern recognition (psychology) , data mining , biology , peptide sequence , genetics , gene , image (mathematics)
A renewed interest in the multiple sequence alignment problem has given rise to several new algorithms. In contrast to traditional progressive methods, computationally expensive score optimization strategies are now predominantly employed. We systematically tested four methods (Poa, Dialign, T‐Coffee and ClustalW) for the speed and quality of their alignments. As test sequences we used structurally derived alignments from BAliBASE and synthetic alignments generated by Rose. The tests included alignments of variable numbers of domains embedded in random spacer sequences. Overall, Dialign was the most accurate in cases with low sequence identity, while T‐Coffee won in cases with high sequence identity. The fast Poa algorithm was almost as accurate, while ClustalW could compete only in strictly global cases with high sequence similarity.