Evidence map›Paper›PMID 16217608›Full record

ArticlePlant molecular biology2005

A pilot study of transcription unit analysis in rice using oligonucleotide tiling-path microarray.

Viktor Stolc, Lei Li, Xiangfeng Wang, Xueyong Li, Ning Su, Waraporn Tongprasit, Bin Han, Yongbiao Xue, Jiayang Li, Michael Snyder and 3 more

Abstract read
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In one paragraph

Article in Plant molecular biology, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
4.1field-weighted citation impact, top 6% 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

8 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Rice functional genomics research in China.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2007
    Article
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  8. 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

13 authors at 4 institutions in 2 countries.

Viktor StolcDepartment of Molecular Cellular and Developmental Biology, Yale University, New Haven, CT 06520, USA.
Lei Li
Xiangfeng Wang
Xueyong Li
Ning Su
Waraporn Tongprasit
Bin Han
Yongbiao Xue
Jiayang Li
Michael Snyder
Mark Gerstein
Jun Wang
Xing Wang Deng
Yale University · USChinese Academy of Sciences · CNNational Center for Gene Research · CNBeijing Institute of Genomics · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the international efforts to sequence the rice genome are completed, an immediate challenge and opportunity is to comprehensively and accurately define all transcription units in the rice genome. Here we describe a strategy of using high-density oligonucleotide tiling-path microarrays to map transcription of the japonica rice genome. In a pilot experiment to test this approach, one array representing the reverse strand of the last 11.2 Mb sequence of chromosome 10 was analyzed in detail based on a mathematical model developed in this study. Analysis of the array data detected 77% of the reference gene models in a mixture of four RNA populations. Moreover, significant transcriptional activities were found in many of the previously annotated intergenic regions. These preliminary results demonstrate the utility of genome tiling microarrays in evaluating annotated rice gene models and in identifying novel transcription units that will facilitate rice genome annotation.

Indexed as

Genome, PlantCarbocyaninesChromosomes, PlantDNA, ComplementaryOligonucleotide Array Sequence AnalysisOryzaPilot ProjectsReproducibility of ResultsRNA, PlantSequence Analysis, DNATranscription, GeneticCarbocyaninescyanine dye 3DNA, ComplementaryRNA, Plant

Identifiers

PMID16217608
OpenAlexW2150001834

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.