ArticleBMC genomics2014
ITEP: an integrated toolkit for exploration of microbial pan-genomes.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.
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Who cites it
70 citing papers in PubMed.
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- Comparative genome analysis reveals broad phylogenetic and functional diversity within the order Nitrospirales.The ISME journal · 2025Article
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- Host-gut microbiota interactions shape parasite infections in farmed Atlantic salmon.mSystems · 2024Article
- Genomic analysis ofMicrobial genomics · 2023Article
- Investigation of differences in susceptibility of Campylobacter jejuni strains to UV light-emitting diode (UV-LED) technology.Scientific reports · 2023Article
- Replicated life-history patterns and subsurface origins of the bacterial sister phyla Nitrospirota and Nitrospinota.The ISME journal · 2023Article
- Co-diversification of an intestinal Mycoplasma and its salmonid host.The ISME journal · 2023Article
- Comparison of antimicrobial resistant Escherichia coli isolated from Irish commercial pig farms with and without zinc oxide and antimicrobial usage.Gut pathogens · 2023Article
- Virulence and genomic diversity among clinical isolates of ST1 (BI/NAP1/027)bioRxiv : the preprint server for biology · 2023Article
- Thiocillin contributes to the ecological fitness ofFrontiers in microbiology · 2023Article
- Associated bacterial communities, confrontation studies, and comparative genomics reveal important interactions betweenFrontiers in fungal biology · 2023Article
- Genomic profiling of Nitrospira species reveals ecological success of comammox Nitrospira.Microbiome · 2022Article
10 more citing papers are in PubMed but not listed here.
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5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundComparative genomics is a powerful approach for studying variation in physiological traits as well as the evolution and ecology of microorganisms. Recent technological advances have enabled sequencing large numbers of related genomes in a single project, requiring computational tools for their integrated analysis. In particular, accurate annotations and identification of gene presence and absence are critical for understanding and modeling the cellular physiology of newly sequenced genomes. Although many tools are available to compare the gene contents of related genomes, new tools are necessary to enable close examination and curation of protein families from large numbers of closely related organisms, to integrate curation with the analysis of gain and loss, and to generate metabolic networks linking the annotations to observed phenotypes.
resultsWe have developed ITEP, an Integrated Toolkit for Exploration of microbial Pan-genomes, to curate protein families, compute similarities to externally-defined domains, analyze gene gain and loss, and generate draft metabolic networks from one or more curated reference network reconstructions in groups of related microbial species among which the combination of core and variable genes constitute the their "pan-genomes". The ITEP toolkit consists of: (1) a series of modular command-line scripts for identification, comparison, curation, and analysis of protein families and their distribution across many genomes; (2) a set of Python libraries for programmatic access to the same data; and (3) pre-packaged scripts to perform common analysis workflows on a collection of genomes. ITEP's capabilities include de novo protein family prediction, ortholog detection, analysis of functional domains, identification of core and variable genes and gene regions, sequence alignments and tree generation, annotation curation, and the integration of cross-genome analysis and metabolic networks for study of metabolic network evolution.
conclusionsITEP is a powerful, flexible toolkit for generation and curation of protein families. ITEP's modular design allows for straightforward extension as analysis methods and tools evolve. By integrating comparative genomics with the development of draft metabolic networks, ITEP harnesses the power of comparative genomics to build confidence in links between genotype and phenotype and helps disambiguate gene annotations when they are evaluated in both evolutionary and metabolic network contexts.
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