Evidence map›Paper›PMID 21687718›Full record

ArticleFrontiers in microbiology2010

The dawning era of comprehensive transcriptome analysis in cellular microbiology.

Chihiro Aikawa, Fumito Maruyama, Ichiro Nakagawa

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

3 authors.

Chihiro AikawaSection of Bacterial Pathogenesis, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University Tokyo, Japan.
Fumito Maruyama
Ichiro Nakagawa

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacteria rapidly change their transcriptional patterns during infection in order to adapt to the host environment. To investigate host-bacteria interactions, various strategies including the use of animal infection models, in vitro assay systems and microscopic observations have been used. However, these studies primarily focused on a few specific genes and molecules in bacteria. High-density tiling arrays and massively parallel sequencing analyses are rapidly improving our understanding of the complex host-bacterial interactions through identification and characterization of bacterial transcriptomes. Information resulting from these high-throughput techniques will continue to provide novel information on the complexity, plasticity, and regulation of bacterial transcriptomes as well as their adaptive responses relative to pathogenecity. Here we summarize recent studies using these new technologies and discuss the utility of transcriptome analysis.

Indexed as

massively parallel sequencingtiling arraytranscriptome

Identifiers

PMID21687718
PMCPMC3109594

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.