Evidence map›Paper›PMID 19575298›Full record

ArticleJournal of biomolecular NMR2009

CheckShift improved: fast chemical shift reference correction with high accuracy.

Simon W Ginzinger, Marko Skocibusić, Volker Heun

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Article in Journal of biomolecular NMR, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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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

3 authors.

Simon W GinzingerDepartment of Molecular Biology Division of Bioinformatics, Center of Applied Molecular Engineering, University of Salzburg, Hellbrunnerstr. 34/3.OG, Salzburg 5020, Osterreich. simon@came.sbg.ac.at
Marko Skocibusić
Volker Heun

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The construction of a consistent protein chemical shift database is an important step toward making more extensive use of this data in structural studies. Unfortunately, progress in this direction has been hampered by the quality of the available data, particularly with respect to chemical shift referencing, which is often either inaccurate or inconsistently annotated. Preprocessing of the data is therefore required to detect and correct referencing errors. In an earlier study we developed CheckShift, a program for performing this task automatically. Now we spent substantial effort in improving the running time of the CheckShift algorithm, which resulted in an running time decrease of 90%, thereby achieving equivalent quality to the former version of CheckShift. The reason for the running time decrease is twofold. Firstly we improved the search for the optimal re-referencing offset considerably. Secondly, as CheckShift is based on a secondary structure prediction from the amino acid sequence (formally PsiPred was used), we evaluated a wide range of available secondary structure prediction programs focusing on the special needs of the CheckShift algorithm. The results of this evaluation prove empirically that we can use faster secondary structure prediction programs than PsiPred without sacrificing CheckShift's accuracy. Very recently Wang and Markley (2009) gave a small list of extreme outliers of the former version of the CheckShift web-server. Those were due to the empirical reduction of the search space implemented in the old version. The new version of CheckShift now gives very similar results to RefDB and LACS for all outliers mentioned in Table 1 of Wang and Markley (2009).

Indexed as

AlgorithmsDatabases, ProteinNuclear Magnetic Resonance, BiomolecularProteinsProtein Structure, SecondaryProteins

Identifiers

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Registered trials

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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.