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BAliBASE 3.0: Latest developments of the multiple sequence alignment benchmark
Abstract
Multiple sequence alignment is one of the cornerstones of modern molecular biology. It is used to identify conserved motifs, to determine protein domains, in 2D/3D structure prediction by homology and in evolutionary studies. Recently, high‐throughput technologies such as genome sequencing and structural proteomics have lead to an explosion in the amount of sequence and structure information available. In response, several new multiple alignment methods have been developed that improve both the efficiency and the quality of protein alignments. Consequently, the benchmarks used to evaluate and compare these methods must also evolve. We present here the latest release of the most widely used multiple alignment benchmark, BAliBASE, which provides high quality, manually refined, reference alignments based on 3D structural superpositions. Version 3.0 of BAliBASE includes new, more challenging test cases, representing the real problems encountered when aligning large sets of complex sequences. Using a novel, semiautomatic update protocol, the number of protein families in the benchmark has been increased and representative test cases are now available that cover most of the protein fold space. The total number of proteins in BAliBASE has also been significantly increased from 1444 to 6255 sequences. In addition, full‐length sequences are now provided for all test cases, which represent difficult cases for both global and local alignment programs. Finally, the BAliBASE Web site (http://www‐bio3d‐igbmc.u‐strasbg.fr/balibase) has been completely redesigned to provide a more user‐friendly, interactive interface for the visualization of the BAliBASE reference alignments and the associated annotations. Proteins 2005. © 2005 Wiley‐Liss, Inc.
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Cites
MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform
Katoh, K. (2002) · Nucleic Acids Research · doi:10.1093/nar/gkf436 · Cited by 17,027
Kabsch, W., & Sander, C. (1983) · Biopolymers · doi:10.1002/bip.360221211 · Cited by 15,320
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Self-citationClustal Omega for making accurate alignments of many protein sequences
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Parallelization of the MAFFT multiple sequence alignment program
Katoh, K., & Toh, H. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq224 · Cited by 928
Sela, I., Ashkenazy, H., Katoh, K., & Pupko, T. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv318 · Cited by 835
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Wright, E. S. (2015) · BMC Bioinformatics · doi:10.1186/s12859-015-0749-z · Cited by 385
An Alignment Confidence Score Capturing Robustness to Guide Tree Uncertainty
Penn, O., Privman, E., Landan, G., Graur, D., & Pupko, T. (2010) · Molecular Biology and Evolution · doi:10.1093/molbev/msq066 · Cited by 331
Tan, G., Muffato, M., Ledergerber, C., Herrero, J., Goldman, N., Gil, M., & Dessimoz, C. (2015) · Systematic Biology · doi:10.1093/sysbio/syv033 · Cited by 261
Thompson, J. D., Linard, B., Lecompte, O., & Poch, O. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018093 · Cited by 242
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Earl, D., Nguyen, N., Hickey, G., Harris, R. S., Fitzgerald, S., Beal, K., Seledtsov, I., Molodtsov, V., Raney, B. J., Clawson, H., et al. (2014) · Genome Research · doi:10.1101/gr.174920.114 · Cited by 113
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Hoen, D. R., Hickey, G., Bourque, G., Casacuberta, J., Cordaux, R., Feschotte, C., Fiston-Lavier, A.-S., Hua-Van, A., Hubley, R., Kapusta, A., et al. (2015) · Mobile DNA · doi:10.1186/s13100-015-0044-6 · Cited by 105
Issues in bioinformatics benchmarking: the case study of multiple sequence alignment
Aniba, M. R., Poch, O., & Thompson, J. D. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq625 · Cited by 72
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Al Ait, L., Yamak, Z., & Morgenstern, B. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt283 · Cited by 58
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Pervez, M. T., Babar, M. E., Nadeem, A., Aslam, M., Awan, A. R., Aslam, N., Hussain, T., Naveed, N., Qadri, S., Waheed, U., et al. (2014) · Evolutionary Bioinformatics · doi:10.4137/ebo.s19199 · Cited by 48
Protein embedding based alignment
Iovino, B. G., & Ye, Y. (2024) · BMC Bioinformatics · doi:10.1186/s12859-024-05699-5 · Cited by 29
Su, W., Liao, X., Lu, Y., Zou, Q., & Peng, S. (2017) · Journal of Computational Biology · doi:10.1089/cmb.2017.0040 · Cited by 21
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“Most of these databases include comparatively similar sequences [31], albeit with the addition of features that are often difficult to align such as repeats, and many of the benchmarks were created using simulation techniques [30].”
BackgroundScoring alignments by embedding vector similarity
(2024) · doi:10.1093/bib/bbae178 · Cited by 8
Protein embeddings and local alignments
Malec, J., Golding, G. B., & Ilie, L. (2026) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.12.002 · Cited by 5
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Metadata
- Authors
- Thompson, J. D., Koehl, P., Ripp, R., & Poch, O.
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2005-07-25
- Volume
- 61
- Issue
- 1
- Pages
- 127-136
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2136570298
- Cited by
- 404
- References
- 2
- FWCI
- 7.95
- Type
- journal article
- Language
- en
- Open access
- closed
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