ReviewImmunological reviews2011
A systems biological view of intracellular pathogens.
Review in Immunological reviews, 2011. 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.
- The multifaceted nature of antimicrobial peptides: current synthetic chemistry approaches and future directions.Chemical Society reviews · 2021Review
- A Review of Using Mathematical Modeling to Improve Our Understanding of Bacteriophage, Bacteria, and Eukaryotic Interactions.Frontiers in microbiology · 2021Review
- Efflux pumps and antimicrobial resistance: Paradoxical components in systems genomics.Progress in biophysics and molecular biology · 2019Review
- Understanding the Cross-Talk of Redox Metabolism and Fe-S Cluster Biogenesis in Leishmania Through Systems Biology Approach.Frontiers in cellular and infection microbiology · 2019Article
- Metabolomics in the fight against malaria.Memorias do Instituto Oswaldo Cruz · 2014Review
- Bugs in the system.Immunological reviews · 2013Review
- Review
- Targeted disruption of Toxoplasma gondii serine protease inhibitor 1 increases bradyzoite cyst formation in vitro and parasite tissue burden in mice.Infection and immunity · 2012Article
- Metabolic responses of primary and transformed cells to intracellular Listeria monocytogenes.PloS one · 2012Article
- Systems analysis of host-parasite interactions.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
2 authors.
Funding
Abstract
As biomedical research becomes increasingly data-intensive, it is increasingly essential to integrate genomic-scale datasets, so as to generate a more holistic picture of complex biological processes. The systems biology paradigm may differ in strategy from traditional reductionist scientific methods, but the goal remains the same: to generate tenable hypotheses driving the experimental elucidation of biological mechanisms. Intracellular pathogens provide an excellent opportunity for systems analysis, as many of these organisms are amenable to genetic manipulation, allowing their biology to be played off against that of the host. Moreover, many of the most fundamental biological properties of these microbes (host cell invasion, immune evasion, intracellular replication, long-term persistence) are directly linked to pathogenesis and readily quantifiable using genomic-scale technologies. In this review, we summarize and discuss some of the available and foreseeable functional genomics datasets pertaining to host-pathogen interactions and suggest that the host-pathogen interface represents a promising, tractable challenge for systems biological analysis. Success will require developing and leveraging new technologies, expanding data acquisition, and increasing public access to comprehensive datasets, to assemble quantitative and testable models of the host-pathogen relationship.
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.