Evidence map›Paper›PMID 23734902›Full record

ArticleBMC bioinformatics2013

Reconstruction of regulatory networks through temporal enrichment profiling and its application to H1N1 influenza viral infection.

Elena Zaslavsky, German Nudelman, Susanna Marquez, Uri Hershberg, Boris M Hartmann, Juilee Thakar, Stuart C Sealfon, Steven H Kleinstein

Abstract read
In one paragraph

Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Boolean Modeling of Cellular and Molecular Pathways Involved in Influenza Infection.Computational and mathematical methods in medicine · 2016
    Article
  6. Article
  7. Article
  8. Innate immune sensing and response to influenza.Current topics in microbiology and immunology · 2015
    Article
  9. 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

8 authors.

Elena ZaslavskyCenter for Translational Systems Biology and Department of Neurology, Mount Sinai School of Medicine, New York, NY 10029, USA. elena.zaslavsky@mssm.edu.
German Nudelman
Susanna Marquez
Uri Hershberg
Boris M Hartmann
Juilee Thakar
Stuart C Sealfon
Steven H Kleinstein

Funding

Mount Sinai Institutes for Clinical and Translational SciencesUL1TR000067 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI SAMPSON, HUGH A · 2012 to 2014
$16.5M
NCATS NIH HHS UL1TR000067
6 · The paper itself

Abstract

backgroundH1N1 influenza viruses were responsible for the 1918 pandemic that caused millions of deaths worldwide and the 2009 pandemic that caused approximately twenty thousand deaths. The cellular response to such virus infections involves extensive genetic reprogramming resulting in an antiviral state that is critical to infection control. Identifying the underlying transcriptional network driving these changes, and how this program is altered by virally-encoded immune antagonists, is a fundamental challenge in systems immunology.

resultsGenome-wide gene expression patterns were measured in human monocyte-derived dendritic cells (DCs) infected in vitro with seasonal H1N1 influenza A/New Caledonia/20/1999. To provide a mechanistic explanation for the timing of gene expression changes over the first 12 hours post-infection, we developed a statistically rigorous enrichment approach integrating genome-wide expression kinetics and time-dependent promoter analysis. Our approach, TIme-Dependent Activity Linker (TIDAL), generates a regulatory network that connects transcription factors associated with each temporal phase of the response into a coherent linked cascade. TIDAL infers 12 transcription factors and 32 regulatory connections that drive the antiviral response to influenza. To demonstrate the generality of this approach, TIDAL was also used to generate a network for the DC response to measles infection. The software implementation of TIDAL is freely available at http://tsb.mssm.edu/primeportal/?q=tidal_prog.

conclusionsWe apply TIDAL to reconstruct the transcriptional programs activated in monocyte-derived human dendritic cells in response to influenza and measles infections. The application of this time-centric network reconstruction method in each case produces a single transcriptional cascade that recapitulates the known biology of the response with high precision and recall, in addition to identifying potentially novel antiviral factors. The ability to reconstruct antiviral networks with TIDAL enables comparative analysis of antiviral responses, such as the differences between pandemic and seasonal influenza infections.

Indexed as

Gene Expression Regulation, ViralGene Regulatory NetworksSoftwareComputational BiologyDendritic CellsHumansInfluenza A Virus, H1N1 SubtypeInfluenza, HumanTranscription FactorsTranscription Factors

Identifiers

PMID23734902
PMCPMC3633009

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.