ReviewSeminars in immunology2013
Recent progress using systems biology approaches to better understand molecular mechanisms of immunity.
Review in Seminars in immunology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- The Role of Omics Approaches to Characterize Molecular Mechanisms of Rare Ovarian Cancers: Recent Advances and Future Perspectives.Biomedicines · 2021Review
- Elucidating host-microbe interactions in vivo by studying population dynamics using neutral genetic tags.Immunology · 2021Review
- A Synchronous IRF4-Dependent Gene Regulatory Network in B and Helper T Cells Orchestrating the Antibody Response.Trends in immunology · 2020Review
- Article
- Cell Polarization and Epigenetic Status Shape the Heterogeneous Response to Type III Interferons in Intestinal Epithelial Cells.Frontiers in immunology · 2017Article
- Vaccinology in the third millennium: scientific and social challenges.Current opinion in virology · 2016Review
- Identifying genetic determinants of autoimmunity and immune dysregulation.Current opinion in immunology · 2015Review
- Coupling of T cell receptor specificity to natural killer T cell development by bivalent histone H3 methylation.The Journal of experimental medicine · 2015Article
- A review on computational systems biology of pathogen-host interactions.Frontiers in microbiology · 2015Review
- Systems-level analysis of innate immunity.Annual review of immunology · 2014Review
- Network representations of immune system complexity.Wiley interdisciplinary reviews. Systems biology and medicineReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The immune system is composed of multiple dynamic molecular and cellular networks, the complexity of which has been revealed by decades of exacting reductionist research. However, understanding of the immune system sufficient to anticipate its response to novel perturbations requires a more integrative or systems approach to immunology. While methods for unbiased high-throughput data acquisition and computational integration of the resulting datasets are still relatively new, they have begun to substantially enhance our understanding of immunological phenomena. Such approaches have expanded our view of interconnected signaling and transcriptional networks and have highlighted the function of non-linear processes such as spatial regulation and feedback loops. In addition, advances in single cell measurement technology have demonstrated potential sources and functions of response heterogeneity in system behavior. The success of the studies reviewed here often depended upon integration of one or more systems biology approaches with more traditional methods. We hope these examples will inspire a broader range of immunologists to probe questions in a quantitative and integrated manner, advancing collective efforts to understand the immune "system".
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.