Paper Info
Title
Uniclust databases of clustered and deeply annotated protein sequences and alignments.
Abstract
We present three clustered protein sequence databases, Uniclust90, Uniclust50, Uniclust30 and three databases of multiple sequence alignments (MSAs), Uniboost10, Uniboost20 and Uniboost30, as a resource for protein sequence analysis, function prediction and sequence searches. The Uniclust databases cluster UniProtKB sequences at the level of 90%, 50% and 30% pairwise sequence identity. Uniclust90 and Uniclust50 clusters showed better consistency of functional annotation than those of UniRef90 and UniRef50, owing to an optimised clustering pipeline that runs with our MMseqs2 software for fast and sensitive protein sequence searching and clustering. Uniclust sequences are annotated with matches to Pfam, SCOP domains, and proteins in the PDB, using our HHblits homology detection tool. Due to its high sensitivity, Uniclust contains 17% more Pfam domain annotations than UniProt. Uni-boost MSAs of three diversities are built by enriching the Uniclust30 MSAs with local sequence matches from MMseqs2 profile searches through Uniclust30. All databases can be downloaded from the Uniclust server at uniclust. mmseqs. com. Users can search clusters by keywords and explore their MSAs, taxonomic representation, and annotations. Uniclust is updated every two months with the new UniProt release.
Year
DOI
Venue
2017
10.1093/nar/gkw1081
NUCLEIC ACIDS RESEARCH
Field
DocType
Volume
Gene,Biology,Computational biology,Genetics,Peptide sequence
Journal
45
Issue
ISSN
Citations 
D1
0305-1048
12
PageRank 
References 
Authors
0.65
8
6
Name
Order
Citations
PageRank
Milot Mirdita1142.40
Lars von den Driesch2120.65
Clovis Galiez3120.65
Maria Jesus Martin42793365.41
Johannes Söding538935.16
Martin Steinegger6172.51