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Cited by 1,453

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

The PredictProtein server

Open access
Rost, B., Yachdav, G., Liu, J.·2004·Nucleic Acids Research

Abstract

PredictProtein (http://www.predictprotein.org) is an Internet service for sequence analysis and the prediction of protein structure and function. Users submit protein sequences or alignments; PredictProtein returns multiple sequence alignments, PROSITE sequence motifs, low-complexity regions (SEG), nuclear localization signals, regions lacking regular structure (NORS) and predictions of secondary structure, solvent accessibility, globular regions, transmembrane helices, coiled-coil regions, structural switch regions, disulfide-bonds, sub-cellular localization and functional annotations. Upon request fold recognition by prediction-based threading, CHOP domain assignments, predictions of transmembrane strands and inter-residue contacts are also available. For all services, users can submit their query either by electronic mail or interactively via the World Wide Web.

Overview

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Registry

Crossref · 10.1093/nar/gkh377

Cites

2 of 2 references verified0 citation errors · 0 not checkable

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Citations

Cites

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Cited by

Metadata

Authors
Rost, B., Yachdav, G., & Liu, J.
Venue
Nucleic Acids Research
Published
2004-07-01
Volume
32
Issue
Web Server
Pages
W321-W326
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
OpenAlex
W2110863368
Cited by
1,453
References
2
FWCI
33.35
Type
journal article
Language
en
Open access
green

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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.

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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.