Evidence map›Paper›PMID 19074493›Full record

ArticleBriefings in bioinformatics2009

Towards the integrated analysis, visualization and reconstruction of microbial gene regulatory networks.

Jan Baumbach, Andreas Tauch, Sven Rahmann

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2009. 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. Molecular networks in Network Medicine: Development and applications.Wiley interdisciplinary reviews. Systems biology and medicine · 2020
    Review
  2. Article
  3. Review
  4. Article
  5. Mechanisms and evolution of control logic in prokaryotic transcriptional regulation.Microbiology and molecular biology reviews : MMBR · 2009
    Review
  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

3 authors.

Jan BaumbachInternational Computer Science Institute, Berkeley, USA. jbaumbac@icsi.berkeley.edu
Andreas Tauch
Sven Rahmann

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To handle changing environmental surroundings and to manage unfavorable conditions, microbial organisms have evolved complex transcriptional regulatory networks. To comprehensively analyze these gene regulatory networks, several online available databases and analysis platforms have been implemented and established. In this article, we address the typical cycle of scientific knowledge exploration and integration in the area of procaryotic transcriptional gene regulation. We briefly review five popular, publicly available systems that support (i) the integration of existing knowledge, (ii) visualization capabilities and (iii) computer analysis to predict promising wet lab targets. We exemplify the benefits of such integrated data analysis platforms by means of four application cases exemplarily performed with the corynebacterial reference database CoryneRegNet.

Indexed as

Databases, GeneticGene Expression Regulation, BacterialGene Regulatory NetworksSoftwareAcetatesBacterial ProteinsComputational BiologyCorynebacteriumDatabase Management SystemsGenome, BacterialGlucoseUser-Computer InterfaceAcetatesBacterial ProteinsGlucose

Identifiers

PMID19074493
PMCPMC2638629

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.