Removing near-neighbour redundancy from large protein sequence collections

By Liisa Holm, Christopher Sander. 1998

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Hidden Markov model speed heuristic and iterative HMM search procedure (2010, methodology): “The non-redundant database, NRDB90, used in this study was created from NCBI’s NR, 1/12/06, database which was filtered to remove sequences with greater than 90% identity using Holm and Sander’s method [7].”
Enhanced Protein Fold Prediction Method Through a Novel Feature Extraction Technique (2015, methodology): “1) PSI-BLAST Based Features: The PSI-BLAST profile of a query amino acid sequence was generated by running the PSI-BLAST program against the protein database nrdb90 [43] with three iterations and a cutoff E-value of 0.”
Assessing the Evolutionary Impact of Amino Acid Mutations in the Human Genome (2008, methodology): “. To assess evolutionary conservation, our sequences were aligned to those in the nrdb95 database (a union of the Swissprot, Swissnew, Trembl, Tremblnew, Genbank, PIR, Wormpep and PDB databases, with sequences of >95% similarity removed;”
HPID: The Human Protein Interaction Database (2004, background): “29.1 (http://www.ensembl.org/), 3877 yeast proteins, SCOP proteins (Lo Conte et al., 2002) and a non-redundant protein sequence database, NRDB90 (Holm and Sander, 1998).”
RSDB: representative protein sequence databases have high information content (2000, methodology): “( Bleasby and Wootton, 1990; Bleasby et al., 1994; Holm and Sander, 1998; Kallberg and Persson, 1999).”
Clustered Sequence Representation for Fast Homology Search (2007, unknown): “, 1996), NRDB90 (Holm and Sander, 1998), RSDB (Park et al.”
The amino-acid mutational spectrum of human genetic disease (2003, methodology): “To characterize the evolutionary conservation of mutation sites we used BLASTGP to search the nrdb90 database [37] for homologs with greater than 30% sequence identity.”
The continuing conundrum of the LEA proteins (2007, methodology): “pl (Holm and Sander 1998) so that no two sequences were more that 90% similar.”
Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences (2006, methodology): “Greedy incremental clustering has been employed in sequence clustering to reduce the number of sequence comparisons since the implementation of a tool by Holm and Sander (1998) to create nrdb90 for protein sequences with a decapeptide filter to further reduce the number of comparisons.”
Analysis and prediction of DNA-binding proteins and their binding residues based on composition, sequence and structural information (2004, methodology): “Solvent accessibility or accessible surface area (ASA) values of 62 protein–DNA complexes were calculated using DSSP program (Kabsch and Sander, 1983).”
Tolerating some redundancy significantly speeds up clustering of large protein databases (2002, background): “NRDB90 (Holm and Sander, 1998) is a database where sequences with 90% identities to a representative were removed.”
Marine DNA viral macro- and micro-diversity from pole to pole (2019, background): “0 viral genes into protein clusters (PCs) based on sequence homology (Sensu) (Holm and Sander, 1998) to identify positively selected zone-specific PCs.”
Sequence clustering strategies improve remote homology recognitions while reducing search times. (2002, methodology): “For example, the nrdb90 program (Holm and Sander, 1998), implemented with short peptide filters and a lookup table, can cluster the NR to the 90% threshold level.”