Evidence map›Paper›PMID 19265557›Full record

ArticleGenome biology2009

DISTILLER: a data integration framework to reveal condition dependency of complex regulons in Escherichia coli.

Karen Lemmens, Tijl De Bie, Thomas Dhollander, Sigrid C De Keersmaecker, Inge M Thijs, Geert Schoofs, Ami De Weerdt, Bart De Moor, Jos Vanderleyden, Julio Collado-Vides and 2 more

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
3.0field-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

33 citing papers in PubMed, 54 citations in OpenAlex.

  1. Review
  2. Using genome-wide expression compendia to study microorganisms.Computational and structural biotechnology journal · 2022
    Review
  3. Network Modeling in Biology: Statistical Methods for Gene and Brain Networks.Statistical science : a review journal of the Institute of Mathematical Statistics · 2021
    Article
  4. Computational biology approaches for mapping transcriptional regulatory networks.Computational and structural biotechnology journal · 2021
    Review
  5. Article
  6. Article
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  9. A graph theoretical approach to data fusion.Statistical applications in genetics and molecular biology · 2016
    Article
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  14. Review
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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

12 authors at 2 institutions in 3 countries.

Karen LemmensDepartment of Electrical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium. karen.lemmens@esat.kuleuven.be
Tijl De Bie
Thomas Dhollander
Sigrid C De Keersmaecker
Inge M Thijs
Geert Schoofs
Ami De Weerdt
Bart De Moor
Jos Vanderleyden
Julio Collado-Vides
Kristof Engelen
Kathleen Marchal
KU Leuven · BEUniversidad Nacional Autónoma de México · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present DISTILLER, a data integration framework for the inference of transcriptional module networks. Experimental validation of predicted targets for the well-studied fumarate nitrate reductase regulator showed the effectiveness of our approach in Escherichia coli. In addition, the condition dependency and modularity of the inferred transcriptional network was studied. Surprisingly, the level of regulatory complexity seemed lower than that which would be expected from RegulonDB, indicating that complex regulatory programs tend to decrease the degree of modularity.

Indexed as

Gene Regulatory NetworksSoftwareChromatin ImmunoprecipitationComputational BiologyEscherichia coliGene Expression Regulation, BacterialRegulonTranscription FactorsTranscription Factors

Identifiers

PMID19265557
PMCPMC2690998
OpenAlexW2117379303

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.