ReviewBriefings in bioinformatics2019
Microbial genomic island discovery, visualization and analysis.
Review in Briefings in bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
What it found
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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.
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Who cites it
57 citing papers in PubMed.
- Phylogenomic framework and virulence gene boundaries of emerging Shiga toxin-producingVirulence · 2026Article
- Pathogenome and Plasmid-Borne Antimicrobial Resistance Phenotypes in a Multidrug-Resistant O111:H8 Shiga Toxin-ProducingbioRxiv : the preprint server for biology · 2026Article
- Comparative pathogenomics and in silico analysis of energy metabolism in Acinetobacter baumannii ST195 and novel Turkish isolates encoding blaOXA-23, blaOXA-66, and blaOXA-852.International microbiology : the official journal of the Spanish Society for Microbiology · 2026Article
- GIPSy2: high-performance and scalable genomic island prediction software.Scientific reports · 2026Article
- Initial identification of genomic islands in Taylorella equigenitalis and Taylorella asinigenitalis and their distribution in isolates from around the world.BMC microbiology · 2026Article
- Evaluating ensemble learning approaches for horizontal gene transfer detection.Scientific reports · 2026Article
- Diversity and ecological roles of hidden viral players in groundwater microbiomes.Nature communications · 2026Article
- Research Progress on the Adaptation Law and Core Mechanism of Animal Models for Exercise Intervention in Inflammatory Bowel Disease: A Systematic Review.Clinical and experimental gastroenterology · 2026Review
- Genomic data representations for horizontal gene transfer detection.NAR genomics and bioinformatics · 2025Article
- Pan-genome analysis of Ralstonia pseudosolanacearum associated with tobacco bacterial wilt in China.BMC microbiology · 2025Article
- Mapping the pangenome of sulfate reducing bacteria: core genes, plasticity, and novel functions in Desulfovibrio spp.World journal of microbiology & biotechnology · 2025Article
- The Role of Genomic Islands in the Pathogenicity and Evolution of Plant-Pathogenic Gammaproteobacteria.Microorganisms · 2025Review
- Draft genome sequence and comparative genomic analysis of Halomonas salifodinae strain A2 isolated from the Zapotitlán Salinas Valley, Puebla, Mexico.Extremophiles : life under extreme conditions · 2025Article
- Carbapenem-ResistantAntibiotics (Basel, Switzerland) · 2025Review
- Current state and future prospects of Horizontal Gene Transfer detection.NAR genomics and bioinformatics · 2025Review
- Structural and bioinformatics analyses identify deoxydinucleotide-specific nucleases and their association with genomic islands in gram-positive bacteria.Nucleic acids research · 2025Article
- Synteruptor: mining genomic islands for non-classical specialized metabolite gene clusters.NAR genomics and bioinformatics · 2024Article
- Pathogenomes of Shiga Toxin Positive and NegativeMicroorganisms · 2024Article
- Pan-Genome Plasticity and Virulence Factors: A Natural Treasure Trove forAntibiotics (Basel, Switzerland) · 2024Review
- First comparative genomics analysis of Corynebacterium auriscanis.Memorias do Instituto Oswaldo Cruz · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Horizontal gene transfer (also called lateral gene transfer) is a major mechanism for microbial genome evolution, enabling rapid adaptation and survival in specific niches. Genomic islands (GIs), commonly defined as clusters of bacterial or archaeal genes of probable horizontal origin, are of particular medical, environmental and/or industrial interest, as they disproportionately encode virulence factors and some antimicrobial resistance genes and may harbor entire metabolic pathways that confer a specific adaptation (solvent resistance, symbiosis properties, etc). As large-scale analyses of microbial genomes increases, such as for genomic epidemiology investigations of infectious disease outbreaks in public health, there is increased appreciation of the need to accurately predict and track GIs. Over the past decade, numerous computational tools have been developed to tackle the challenges inherent in accurate GI prediction. We review here the main types of GI prediction methods and discuss their advantages and limitations for a routine analysis of microbial genomes in this era of rapid whole-genome sequencing. An assessment is provided of 20 GI prediction software methods that use sequence-composition bias to identify the GIs, using a reference GI data set from 104 genomes obtained using an independent comparative genomics approach. Finally, we present guidelines to assist researchers in effectively identifying these key genomic regions.
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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.