Evidence map›Paper›PMID 12003488›Full record

ArticleRNA (New York, N.Y.)2002

Mining biochemical information: lessons taught by the ribosome.

Michelle Whirl-Carrillo, Irene S Gabashvili, Michael Bada, D Rey Banatao, Russ B Altman

Abstract readComparative Study
In one paragraph

Article in RNA (New York, N.Y.), 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. The RNA Base-Pairing Problem and Base-Pairing Solutions.Cold Spring Harbor perspectives in biology · 2018
    Review
  2. Article
  3. Article
  4. RNA crosslinking methods.Methods in enzymology · 2009
    Article
  5. Structural inference of native and partially folded RNA by high-throughput contact mapping.Proceedings of the National Academy of Sciences of the United States of America · 2008
    Article
  6. Article
  7. 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.

Michelle Whirl-CarrilloStanford Medical Informatics, Stanford University, California 94305-5479, USA.
Irene S Gabashvili
Michael Bada
D Rey Banatao
Russ B Altman

Funding

INSTITUTIONAL TRAINING GRANT IN GENOME SCIENCET32HG000044 · NHGRI · STANFORD UNIVERSITY · PI MICHAEL P. SNYDER · 1995 to 2026
$32.2M
Maximizing Opportunities for Research Excellence - Evaluation Training SupplementR25GM056847 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DUNCAN, D'ANNE S., SELLO, JASON K · 1998 to 2023
$14.1M
Molecular Biophysics Training Program at StanfordT32GM008294 · NIGMS · STANFORD UNIVERSITY · PI HUANG, KERWYN C. · 1989 to 2019
$7.4M
Text Mining for High-fidelity Curation and Discovery of Gene-drug-phenotype RelationshipsR01LM005652 · NLM · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO · 2000 to 2018
$6.2M
MODELING AND COMPUTING WITH UNCERTAIN STRUCTURESR29LM005652 · NLM · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO · 1994 to 1998
–
NHGRI NIH HHS T32 HG 00044NIGMS NIH HHS 2 R25 GM056847-04NIGMS NIH HHS GM-08294NLM NIH HHS LM-05652NLM NIH HHS LM-06422
6 · The paper itself

Abstract

The publication of the crystal structures of the ribosome offers an opportunity to retrospectively evaluate the information content of hundreds of qualitative biochemical and biophysical studies of these structures. We assessed the correspondence between more than 2,500 experimental proximity measurements and the distances observed in the ribosomal crystals. Although detailed experimental procedures and protocols are unique in almost each analyzed paper, the data can be grouped into subsets with similar patterns and analyzed in an integrative fashion. We found that, for crosslinking, footprinting, and cleavage data, the corresponding distances observed in crystal structures generally did not exceed the maximum values expected (from the estimated length of the agent and maximal anticipated deviations from the conformations found in crystals). However, the distribution of distances had heavier tails than those typically assumed when building three-dimensional models, and the fraction of incompatible distances was greater than expected. Some of these incompatibilities can be attributed to the experimental methods used. In addition, the accuracy of these procedures appears to be sensitive to the different reactivities, flexibilities, and interactions among the components. These findings demonstrate the necessity of a very careful analysis of data used for structural modeling and consideration of all possible parameters that could potentially influence the quality of measurements. We conclude that experimental proximity measurements can provide useful distance information for structural modeling, but with a broad distribution of inferred distance ranges. We also conclude that development of automated modeling approaches would benefit from better annotations of experimental data for detection and interpretation of their significance.

Indexed as

AlgorithmsDatabases, FactualData Interpretation, StatisticalDNA FootprintingHumansModels, MolecularProtein BiosynthesisProteinsRibosomesRNAProteinsRNA

Identifiers

PMID12003488
PMCPMC1370250

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.