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Title: GitHub - soedinglab/MMseqs2: MMseqs2: ultra fast and sensitive search and clustering suite · GitHub

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Description: MMseqs2: ultra fast and sensitive search and clustering suite - soedinglab/MMseqs2

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https://github.com/soedinglab/mmseqs2#publications
Steinegger M and Soeding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnology, doi: 10.1038/nbt.3988 (2017)https://www.nature.com/articles/nbt.3988
Steinegger M and Soeding J. Clustering huge protein sequence sets in linear time. Nature Communications, doi: 10.1038/s41467-018-04964-5 (2018)https://www.nature.com/articles/s41467-018-04964-5
Mirdita M, Steinegger M and Soeding J. MMseqs2 desktop and local web server app for fast, interactive sequence searches. Bioinformatics, doi: 10.1093/bioinformatics/bty1057 (2019)https://academic.oup.com/bioinformatics/article/35/16/2856/5280135
Mirdita M, Steinegger M, Breitwieser F, Soding J, Levy Karin E: Fast and sensitive taxonomic assignment to metagenomic contigs. Bioinformatics, doi: 10.1093/bioinformatics/btab184 (2021)https://doi.org/10.1093/bioinformatics/btab184
Kallenborn F, Chacon A, Hundt C, Sirelkhatim H, Didi K, Cha S, Dallago C, Mirdita M, Schmidt B, Steinegger M: GPU-accelerated homology search with MMseqs2. Nature Methods, doi: 10.1038/s41592-025-02819-8 (2025)https://www.nature.com/articles/s41592-025-02819-8
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