Evidence map›Paper›PMID 11972348›Full record

ArticleNucleic acids research2002

Searching for RNA genes using base-composition statistics.

Peter Schattner

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in Nucleic acids research, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
2.7field-weighted citation impact, top 9% of its field
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

52 citing papers in PubMed, 109 citations in OpenAlex.

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  18. Small RNAs for defence and regulation in archaea.Extremophiles : life under extreme conditions · 2012
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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

1 author at 1 institution in 1 country.

Peter SchattnerCenter for Biomolecular Science and Engineering, 227 Sinsheimer Laboratories, University of California, 1156 High Street, Santa Cruz, CA 95064, USA. schattner@cse.ucsc.edu
University of California, Santa Cruz · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The hypothesis that genomic regions rich in non-protein-coding RNAs (ncRNAs) can be identified using local variations in single-base and dinucleotide statistics has been investigated. (G+C)%, (G-C)% difference, (A-T)% difference and dinucleotide-frequency statistics were compared among seven classes of ncRNAs and three genomes. Significant variations were observed in (G+C)% and, in Methanococcus jannaschii, in the frequency of the dinucleotide 'CG'. Screening programs based on these two base-composition statistics were developed. With (G+C)% screening alone, a 1% fraction of the M.jannaschii genome containing all 44 known transfer RNAs, ribosomal RNAs and signal recognition particle RNAs could be identified. When (G+C)% combined with CG dinucleotide-frequency screening was used, 43 of the 44 known M.jannaschii structural ncRNAs were again identified, while the number of presumably false hits overlapping a known or putative protein-coding gene was reduced from 15 to 6. In addition, 19 candidate ncRNAs were identified including one with significant homology to several known archaeal RNaseP RNAs.

Indexed as

Models, StatisticalAnimalsBase CompositionBase SequenceCaenorhabditis elegansFeasibility StudiesGC Rich SequenceGenetic VariationGenomeMethanococcusMolecular Sequence DataPlasmodium falciparumRNA, RibosomalRNA, TransferRNA, UntranslatedSequence AlignmentRNA, RibosomalRNA, TransferRNA, Untranslated

Identifiers

PMID11972348
PMCPMC113829
OpenAlexW2020812606

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.