ReviewImmunological reviews2013
Bugs in the system.
Review in Immunological reviews, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed, 56 citations in OpenAlex.
- Antagonism of stress granules key for SARS-CoV-2 infection and pathogenesis.bioRxiv : the preprint server for biology · 2026Article
- Mechanisms of Antiviral Immune Evasion of SARS-CoV-2.Journal of molecular biology · 2022Review
- A new perspective for mitigation of SARS-CoV-2 infection: priming the innate immune system for viral attack.Open biology · 2020Article
- Viral metagenomics, protein structure, and reverse genetics: Key strategies for investigating coronaviruses.Virology · 2018Review
- MERS-CoV and H5N1 influenza virus antagonize antigen presentation by altering the epigenetic landscape.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Epigenetic Landscape during Coronavirus Infection.Pathogens (Basel, Switzerland) · 2017Article
- The Nonstructural Proteins Directing Coronavirus RNA Synthesis and Processing.Advances in virus research · 2016Review
- Continuous and Discontinuous RNA Synthesis in Coronaviruses.Annual review of virology · 2015Review
- Article
- Immunity to viruses.Immunological reviews · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Immunity to respiratory virus infection is governed by complex biological networks that influence disease progression and pathogenesis. Systems biology provides an opportunity to explore and understand these multifaceted interactions based on integration and modeling of multiple biological parameters. In this review, we describe new and refined systems-based approaches used to model, identify, and validate novel targets within complex networks following influenza and coronavirus infection. In addition, we propose avenues for extension and expansion that can revolutionize our understanding of infectious disease processes. Together, we hope to provide a window into the unique and expansive opportunity presented by systems biology to understand complex disease processes within the context of infectious diseases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.