ArticleBMC bioinformatics2006
Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models.
Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 221 papers, 1 of them a synthesis that pooled it.
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Who cites it
221 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Fast, flexible gene cluster family delineation with IGUA.Nucleic acids research · 2026Article
- GIPSy2: high-performance and scalable genomic island prediction software.Scientific reports · 2026Article
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- Whole-genome characterization and analysis of Pantoea agglomerans R6: a genomic insight into its pathogenicity and resistance as a potential opportunistic plant pathogen.BMC genomics · 2026Article
- In silico elucidation of polyhydroxyalkanoate biosynthesis pathways in Brevibacterium daeguense and Brevibacterium yomogidense.World journal of microbiology & biotechnology · 2026Article
- Microbial diversity of plant pathogens and insect endosymbionts in Reptalus artemisiae.BMC microbiology · 2026Article
- A Possible Recently Identified Evolutionary Strategy Using Membrane-Bound Vesicle Transfer of Genetic Material to Induce Bacterial Resistance, Virulence and Pathogenicity inInternational journal of molecular sciences · 2026Article
- Genomic signatures of radiation stress adaptations inFrontiers in microbiology · 2026Article
- A machine learning framework for interpreting phylogenetic tree patterns in interkingdom horizontal gene transfer.Frontiers in bioinformatics · 2026Article
- Genomic data representations for horizontal gene transfer detection.NAR genomics and bioinformatics · 2025Article
- Genomic Insights into an EnvironmentalAntibiotics (Basel, Switzerland) · 2025Article
- The acquisition of additional control over quorum sensing regulation reduces the variability of final cell density in Burkholderia.Communications biology · 2025Article
- MOBHunter: a data integration platform for identification and classification of mobile genetic elements in microbial genomes.Nucleic acids research · 2025Article
- Article
- Current state and future prospects of Horizontal Gene Transfer detection.NAR genomics and bioinformatics · 2025Review
- Genomic and transcriptomic insights into the virulence and adaptation of shock syndrome-causingMicrobiology (Reading, England) · 2025Article
- Geographic diversity of theFrontiers in veterinary science · 2025Article
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- Whole-Genome Sequencing ofMicroorganisms · 2024Article
161 more citing papers are in PubMed but not listed here.
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHorizontal gene transfer (HGT) is considered a strong evolutionary force shaping the content of microbial genomes in a substantial manner. It is the difference in speed enabling the rapid adaptation to changing environmental demands that distinguishes HGT from gene genesis, duplications or mutations. For a precise characterization, algorithms are needed that identify transfer events with high reliability. Frequently, the transferred pieces of DNA have a considerable length, comprise several genes and are called genomic islands (GIs) or more specifically pathogenicity or symbiotic islands.
resultsWe have implemented the program SIGI-HMM that predicts GIs and the putative donor of each individual alien gene. It is based on the analysis of codon usage (CU) of each individual gene of a genome under study. CU of each gene is compared against a carefully selected set of CU tables representing microbial donors or highly expressed genes. Multiple tests are used to identify putatively alien genes, to predict putative donors and to mask putatively highly expressed genes. Thus, we determine the states and emission probabilities of an inhomogeneous hidden Markov model working on gene level. For the transition probabilities, we draw upon classical test theory with the intention of integrating a sensitivity controller in a consistent manner. SIGI-HMM was written in JAVA and is publicly available. It accepts as input any file created according to the EMBL-format.It generates output in the common GFF format readable for genome browsers. Benchmark tests showed that the output of SIGI-HMM is in agreement with known findings. Its predictions were both consistent with annotated GIs and with predictions generated by different methods.
conclusionSIGI-HMM is a sensitive tool for the identification of GIs in microbial genomes. It allows to interactively analyze genomes in detail and to generate or to test hypotheses about the origin of acquired genes.
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