Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 20,826

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Search and clustering orders of magnitude faster than BLAST

Open access
Edgar, Robert C.·2010·Bioinformatics
DOI 10.1093/bioinformatics/btq461
Open this paper in CoChat — free account

Abstract

Motivation: Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. Results: UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Availability: Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch Contact: robert@drive5.com Supplementary information: Supplementary data are available at Bioinformatics online.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/bioinformatics/btq461

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Research works printed but not linked: 6

  1. Butte, 2001, Challenges in bioinformatics: infrastructure, models and analytics, Trends Biotechnol., 19, 159, 10.1016/S0167-7799(01)01603-1 · DOI
  2. Edgar, 2004, Local homology recognition and distance measures in linear time using compressed amino acid alphabets, Nucleic Acids Res., 32, 380, 10.1093/nar/gkh180 · DOI
  3. Edgar, 2004, MUSCLE: multiple sequence alignment with high accuracy and high throughput, Nucleic Acids Res., 32, 1792, 10.1093/nar/gkh340 · DOI · Paper page
  4. Finn, 2008, The Pfam protein families database, Nucleic Acids Res., 36, D281, 10.1093/nar/gkm960 · DOI
  5. Gardner, 2009, Rfam: updates to the RNA families database, Nucleic Acids Res., 37, D136, 10.1093/nar/gkn766 · DOI
  6. Li, 2006, Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences, Bioinformatics, 22, 1658, 10.1093/bioinformatics/btl158 · DOI · Paper page

Cited by

Items 301–400 of 498

Metadata

Authors
Edgar, R. C.
Venue
Bioinformatics
Publisher
Oxford University Press (OUP)
Published
2010-08-12
Volume
26
Issue
19
Pages
2460-2461
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
DOI
10.1093/bioinformatics/btq461
OpenAlex
W2124351063
Cited by
20,826
References
2
FWCI
86.49
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.