Evidence map›Paper›PMID 20232231›Full record

ArticleJournal of biomolecular NMR2010

SAGA: rapid automatic mainchain NMR assignment for large proteins.

Gordon M Crippen, Aikaterini Rousaki, Matthew Revington, Yongbo Zhang, Erik R P Zuiderweg

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of biomolecular NMR, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Heat shock protein 70 kDa chaperone/DnaJ cochaperone complex employs an unusual dynamic interface.Proceedings of the National Academy of Sciences of the United States of America · 2011
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Gordon M CrippenCollege of Pharmacy, University of Michigan, Ann Arbor, MI 48109, USA. gcrippen@umich.edu
Aikaterini Rousaki
Matthew Revington
Yongbo Zhang
Erik R P Zuiderweg

Funding

Molecular Chaperones and Small MoleculesR01NS059690 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jason E Gestwicki · 2008 to 2026
$7.9M
Study of Allosteric Proteins by NMRR01GM063027 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZUIDERWEG, ERIK R · 2001 to 2010
$2.8M
NIGMS NIH HHS GM063027NIGMS NIH HHS GM063027-08S1NINDS NIH HHS NS059690
6 · The paper itself

Abstract

Here we describe a new algorithm for automatically determining the mainchain sequential assignment of NMR spectra for proteins. Using only the customary triple resonance experiments, assignments can be quickly found for not only small proteins having rather complete data, but also for large proteins, even when only half the residues can be assigned. The result of the calculation is not the single best assignment according to some criterion, but rather a large number of satisfactory assignments that are summarized in such a way as to help the user identify portions of the sequence that are assigned with confidence, vs. other portions where the assignment has some correlated alternatives. Thus very imperfect initial data can be used to suggest future experiments.

Indexed as

AlgorithmsElectronic Data ProcessingSequence Analysis, ProteinAmino Acid SequenceAnimalsComputer SimulationHumansMagnetic Resonance SpectroscopyModels, ChemicalMolecular Sequence DataMolecular WeightPeptide MappingProteinsSensitivity and SpecificityUbiquitinProteinsUbiquitin

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.