Evidence map›Paper›PMID 24448569›Full record

ReviewNature immunology2014

Unifying immunology with informatics and multiscale biology.

Brian A Kidd, Lauren A Peters, Eric E Schadt, Joel T Dudley

Erratum issuedAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Nature immunology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 78 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
78citing papers in PubMed, 1 pooled it
–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

78 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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18 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

4 authors.

Brian A Kidd1] Department of Genetics and Genomic Sciences, New York, New York, USA. [2] Icahn Institute for Genomics and Multiscale Biology, New York, New York, USA. [3] Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Lauren A Peters1] Icahn School of Medicine at Mount Sinai, New York, New York, USA. [2] Graduate School of Biomedical Sciences, New York, New York, USA.
Eric E Schadt1] Department of Genetics and Genomic Sciences, New York, New York, USA. [2] Icahn Institute for Genomics and Multiscale Biology, New York, New York, USA. [3] Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Joel T Dudley1] Department of Genetics and Genomic Sciences, New York, New York, USA. [2] Icahn Institute for Genomics and Multiscale Biology, New York, New York, USA. [3] Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Funding

Methods for Evolutionary Informed Network Analysis to Discover Disease VariationR01DK098242 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI DUDLEY, JOEL THOMAS · 2013 to 2016
$1.7M
NIDDK NIH HHS R01 DK098242
6 · The paper itself

Abstract

The immune system is a highly complex and dynamic system. Historically, the most common scientific and clinical practice has been to evaluate its individual components. This kind of approach cannot always expose the interconnecting pathways that control immune-system responses and does not reveal how the immune system works across multiple biological systems and scales. High-throughput technologies can be used to measure thousands of parameters of the immune system at a genome-wide scale. These system-wide surveys yield massive amounts of quantitative data that provide a means to monitor and probe immune-system function. New integrative analyses can help synthesize and transform these data into valuable biological insight. Here we review some of the computational analysis tools for high-dimensional data and how they can be applied to immunology.

Indexed as

Allergy and ImmunologyImmune SystemAnimalsGenome-Wide Association StudyHigh-Throughput Screening AssaysHumansMedical InformaticsPrincipal Component AnalysisResearch DesignSystems Biology

Identifiers

PMID24448569
PMCPMC4345400

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.