Evidence map›Paper›PMID 32717640›Full record

ReviewiScience2020

Network Approaches for Dissecting the Immune System.

Hao Shi, Koon-Kiu Yan, Liang Ding, Chenxi Qian, Hongbo Chi, Jiyang Yu

Open access · goldAbstract readReview
In one paragraph

Review in iScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
2.6field-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

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 50 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. The Role of Tumor Metabolic Reprogramming in Tumor Immunity.International journal of molecular sciences · 2023
    Review
  13. Article
  14. Embracing complexity in sepsis.Critical care (London, England) · 2023
    Review
  15. Review
  16. Review
  17. Review
  18. Article
  19. Review
  20. Review
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

6 authors at 1 institution in 1 country.

Hao ShiDepartments of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA; Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.
Koon-Kiu YanDepartments of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.
Liang DingDepartments of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.
Chenxi QianDepartments of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA; Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.
Hongbo ChiDepartment of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.
Jiyang YuDepartments of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA. Electronic address: jiyang.yu@stjude.org.
St. Jude Children's Research Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The immune system is a complex biological network composed of hierarchically organized genes, proteins, and cellular components that combat external pathogens and monitor the onset of internal disease. To meet and ultimately defeat these challenges, the immune system orchestrates an exquisitely complex interplay of numerous cells, often with highly specialized functions, in a tissue-specific manner. One of the major methodologies of systems immunology is to measure quantitatively the components and interaction levels in the immunologic networks to construct a computational network and predict the response of the components to perturbations. The recent advances in high-throughput sequencing techniques have provided us with a powerful approach to dissecting the complexity of the immune system. Here we summarize the latest progress in integrating omics data and network approaches to construct networks and to infer the underlying signaling and transcriptional landscape, as well as cell-cell communication, in the immune system, with a focus on hematopoiesis, adaptive immunity, and tumor immunology. Understanding the network regulation of immune cells has provided new insights into immune homeostasis and disease, with important therapeutic implications for inflammation, cancer, and other immune-mediated disorders.

Indexed as

Biological SciencesImmunologySystems Biology

Identifiers

PMID32717640
PMCPMC7390880
OpenAlexW3041166024

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.