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Fast, scalable generation of high‐quality protein multiple sequence alignments using Clustal Omega
Open accessAbstract
Multiple sequence alignments are fundamental to many sequence analysis methods. Most alignments are computed using the progressive alignment heuristic. These methods are starting to become a bottleneck in some analysis pipelines when faced with data sets of the size of many thousands of sequences. Some methods allow computation of larger data sets while sacrificing quality, and others produce high-quality alignments, but scale badly with the number of sequences. In this paper, we describe a new program called Clustal Omega, which can align virtually any number of protein sequences quickly and that delivers accurate alignments. The accuracy of the package on smaller test cases is similar to that of the high-quality aligners. On larger data sets, Clustal Omega outperforms other packages in terms of execution time and quality. Clustal Omega also has powerful features for adding sequences to and exploiting information in existing alignments, making use of the vast amount of precomputed information in public databases like Pfam.
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Strain-Specific Anti-Inflammatory Effects of Faecalibacterium prausnitzii Strain KBL1027 in Koreans
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Evolution and Diversity of Semaphorins and Plexins in Choanoflagellates
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Metadata
- Authors
- Sievers, F., Wilm, A., Dineen, D., Gibson, T. J., Karplus, K., Li, W., Lopez, R., McWilliam, H., Remmert, M., Söding, J., Thompson, J. D., & Higgins, D. G.
- Venue
- Molecular Systems Biology
- Published
- 2011-01
- Volume
- 7
- Issue
- 1
- Pages
- 539-539
- ISSN
- 1744-4292 (ISSN-L)
- OpenAlex
- W2127322768
- Cited by
- 15,355
- References
- 2
- FWCI
- 120.85
- Type
- journal article
- Language
- en
- Open access
- gold
- Licence
- creativecommons.org/licenses/by-nc-sa/3.0/ (tdm)
- creativecommons.org/licenses/by-nc-sa/3.0/ (vor)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.