ReviewMicroorganisms2022
Systems Biology: New Insight into Antibiotic Resistance.
Review in Microorganisms, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Computational Genomics for Resistome Characterization: Current Advancements and Future Challenges Under a One Health Perspective.Antibiotics (Basel, Switzerland) · 2026Review
- Transcriptome-Integrated Metabolic Modeling Identifies Candidate Metabolic Adjuvants in Antibiotic-ResistantAntibiotics (Basel, Switzerland) · 2026Article
- From Microbes to Medicine: Targeting Metalloprotein Pathways for Innovative Antibacterial Strategies.International journal of molecular sciences · 2026Review
- Combined transcriptome and metabolome analysis revealed the antimicrobial mechanism of Griseorhodin C against Methicillin-resistant Staphylococcus aureus.Scientific reports · 2024Article
- ProkDBP: Toward more precise identification of prokaryotic DNA binding proteins.Protein science : a publication of the Protein Society · 2024Article
- Flankophile: a bioinformatic pipeline for prokaryotic genomic synteny analysis.Microbiology spectrum · 2024Article
- Whole Genome Sequencing: Applications in Clinical Bacteriology.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2024Review
- Quantitative systems-based prediction of antimicrobial resistance evolution.NPJ systems biology and applications · 2023Review
- The Multiomics Response ofMicroorganisms · 2023Article
- Design and Synthesis of Novel Antimicrobial Agents.Antibiotics (Basel, Switzerland) · 2023Review
- Bacterial and antibiotic susceptibility test patterns and quality of life of diabetic foot ulcer patients.Journal of advanced pharmaceutical technology & researchArticle
- The protective role of commensal gut microbes and their metabolites against bacterial pathogens.Gut microbesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Over the past few decades, antimicrobial resistance (AMR) has emerged as an important threat to public health, resulting from the global propagation of multidrug-resistant strains of various bacterial species. Knowledge of the intrinsic factors leading to this resistance is necessary to overcome these new strains. This has contributed to the increased use of omics technologies and their extrapolation to the system level. Understanding the mechanisms involved in antimicrobial resistance acquired by microorganisms at the system level is essential to obtain answers and explore options to combat this resistance. Therefore, the use of robust whole-genome sequencing approaches and other omics techniques such as transcriptomics, proteomics, and metabolomics provide fundamental insights into the physiology of antimicrobial resistance. To improve the efficiency of data obtained through omics approaches, and thus gain a predictive understanding of bacterial responses to antibiotics, the integration of mathematical models with genome-scale metabolic models (GEMs) is essential. In this context, here we outline recent efforts that have demonstrated that the use of omics technology and systems biology, as quantitative and robust hypothesis-generating frameworks, can improve the understanding of antibiotic resistance, and it is hoped that this emerging field can provide support for these new efforts.
Indexed as
Identifiers
What Socratic 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 Socratic graph.