ReviewFrontiers in microbiology2018
Network Analyses in Plant Pathogens.
Review in Frontiers in microbiology, 2018. 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.
- Blooming resilience: transcriptomic insights into cotton flower responses to boll weevil infestation.Plant cell reports · 2025Article
- Computational insights into host-pathogen protein interactions: unveiling penaeid shrimp and white spot syndrome virus interplay.Molecular genetics and genomics : MGG · 2025Article
- Integrative Analysis of Transcriptomic Profiles and Physiological Responses Provide New Insights into Drought Stress Tolerance in Oil Palm (International journal of molecular sciences · 2024Article
- Metabolomics of early blight (Alternaria solani) susceptible tomato (Solanum lycopersicum) unfolds key biomarker metabolites and involved metabolic pathways.Scientific reports · 2023Article
- Polygenic pathogen networks influence transcriptional plasticity in the Arabidopsis-Botrytis pathosystem.Genetics · 2023Article
- Molecular network of the oil palm root response to aluminum stress.BMC plant biology · 2023Article
- Genomic Evaluation ofPlants (Basel, Switzerland) · 2023Article
- Advances in Multi-Omics Approaches for Molecular Breeding of Black Rot Resistance inFrontiers in plant science · 2021Review
- A Biocontrol Strain ofPathogens (Basel, Switzerland) · 2020Article
- Understanding Host-Pathogen Interactions inPlants (Basel, Switzerland) · 2020Review
- Bioimaging structural signatures of the oomycete pathogen Sclerospora graminicola in pearl millet using different microscopic techniques.Scientific reports · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Even in the age of big data in Biology, studying the connections between the biological processes and the molecular mechanisms behind them is a challenging task. Systems biology arose as a transversal discipline between biology, chemistry, computer science, mathematics, and physics to facilitate the elucidation of such connections. A scenario, where the application of systems biology constitutes a very powerful tool, is the study of interactions between hosts and pathogens using network approaches. Interactions between pathogenic bacteria and their hosts, both in agricultural and human health contexts are of great interest to researchers worldwide. Large amounts of data have been generated in the last few years within this area of research. However, studies have been relatively limited to simple interactions. This has left great amounts of data that remain to be utilized. Here, we review the main techniques in network analysis and their complementary experimental assays used to investigate bacterial-plant interactions. Other host-pathogen interactions are presented in those cases where few or no examples of plant pathogens exist. Furthermore, we present key results that have been obtained with these techniques and how these can help in the design of new strategies to control bacterial pathogens. The review comprises metabolic simulation, protein-protein interactions, regulatory control of gene expression, host-pathogen modeling, and genome evolution in bacteria. The aim of this review is to offer scientists working on plant-pathogen interactions basic concepts around network biology, as well as an array of techniques that will be useful for a better and more complete interpretation of their data.
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Registered trials
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