Evidence map›Paper›PMID 26362267›Full record

ArticleImmunity2015

Interactive Big Data Resource to Elucidate Human Immune Pathways and Diseases.

Dmitriy Gorenshteyn, Elena Zaslavsky, Miguel Fribourg, Christopher Y Park, Aaron K Wong, Alicja Tadych, Boris M Hartmann, Randy A Albrecht, Adolfo García-Sastre, Steven H Kleinstein and 2 more

Open access · bronzeAbstract read
In one paragraph

Article in Immunity, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 53 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
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  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Silencing the lncRNAJournal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2020
    Article
  11. Article
  12. Review
  13. Article
  14. CD8Leukemia · 2019
    Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

12 authors at 5 institutions in 1 country.

Dmitriy GorenshteynLewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.
Elena ZaslavskyDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Miguel FribourgDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Christopher Y ParkNew York Genome Center, 101 Avenue of the Americas, New York, NY 10013, USA.
Aaron K WongSimons Center for Data Analysis, Simons Foundation, New York, NY 10010, USA.
Alicja TadychLewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.
Boris M HartmannDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Randy A AlbrechtDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Adolfo García-SastreDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Medicine, Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Steven H KleinsteinDepartments of Pathology and Immunobiology, Yale School of Medicine, New Haven, CT 06520, USA; Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.
Olga G TroyanskayaLewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA; Simons Center for Data Analysis, Simons Foundation, New York, NY 10010, USA; Department of Computer Science, Princeton University, Princeton, NJ 08540, USA. Electronic address: ogt@cs.princeton.edu.
Stuart C SealfonDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. Electronic address: stuart.sealfon@mssm.edu.
Icahn School of Medicine at Mount Sinai · USPrinceton University · USSimons Foundation · USNew York Genome Center · USYale University · US

Funding

Project I: Immunity to Influenza in Primary Lung Epithelial CellsU19AI117873 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI HAYOT, FERNAND · 2015 to 2019
$8.6M
lntegration and Visualization of Diverse Biological DataR01GM071966 · NIGMS · PRINCETON UNIVERSITY · PI TROYANSKAYA, OLGA G · 2005 to 2022
$6.4M
Training Program in Mental Health ResearchT32MH096678 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI SALTON, STEPHEN R, SHAPIRO, MATTHEW L · 2012 to 2016
$1.1M
NIAID NIH HHS 1U19AI117873NIAID NIH HHS HHSN272201000054CNIAID NIH HHS U19 AI117873NIGMS NIH HHS R01 GM071966NIMH NIH HHS T32 MH096678
6 · The paper itself

Abstract

Many functionally important interactions between genes and proteins involved in immunological diseases and processes are unknown. The exponential growth in public high-throughput data offers an opportunity to expand this knowledge. To unlock human-immunology-relevant insight contained in the global biomedical research effort, including all public high-throughput datasets, we performed immunological-pathway-focused Bayesian integration of a comprehensive, heterogeneous compendium comprising 38,088 genome-scale experiments. The distillation of this knowledge into immunological networks of functional relationships between molecular entities (ImmuNet), and tools to mine this resource, are accessible to the public at http://immunet.princeton.edu. The predictive capacity of ImmuNet, established by rigorous statistical validation, is easily accessed by experimentalists to generate data-driven hypotheses. We demonstrate the power of this approach through the identification of unique host-virus interaction responses, and we show how ImmuNet complements genetic studies by predicting disease-associated genes. ImmuNet should be widely beneficial for investigating the mechanisms of the human immune system and immunological diseases.

Indexed as

AlgorithmsBayes TheoremComputational BiologyGene Regulatory NetworksHost-Pathogen InteractionsHumansImmune SystemImmune System DiseasesInternetProtein Interaction MappingProtein Interaction MapsReproducibility of ResultsSignal TransductionSupport Vector MachineTranscriptomeVirus Diseases

Identifiers

PMID26362267
PMCPMC4753773
OpenAlexW1855413151

What OpenQuestion holds

Textmetadata
LicenceTDM
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.