MMseqs software suite for fast and deep clustering and searching of large protein sequence sets

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Uniclust databases of clustered and deeply annotated protein sequences and alignments (2016, methodology): “We employ the updating workflow ‘mmseqs clusterupdate’ in the MMseqs2 package for that purpose, which has the added advantage of running in linear time instead of quadratic in the number of sequences.”
Clustering huge protein sequence sets in linear time (2017, methodology): “This algorithm was already implemented for MMseqs [11].”
Fast and accurate protein structure search with Foldseek (2022, unknown): “33).”
Clustering predicted structures at the scale of the known protein universe (2023, unknown): “42) clustering.”
Boltz-1 Democratizing Biomolecular Interaction Modeling (2024, unknown): “We first cluster the protein sequences in PDB by sequence identity with the command mmseqs easy-cluster ... --min-seq-id 0.4 [Hauser et al., 2016].”
Gearing up to handle the mosaic nature of life in the quest for orthologs (2017, methodology): “Another approach dealing with a similar problem was presented in the form of the MMseqs many-versus-many sequence comparison software (Hauser et al., 2016).”
Sensitive protein alignments at tree-of-life scale using DIAMOND (2021, methodology): “In addition, we also use a method of composition-based score adjustments 15 that is designed to increase the specificity of the scoring procedure.”