ArticleMicrobial genomics2021
The Dynamic Codon Biaser: calculating prokaryotic codon usage biases.
Article in Microbial genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Live tracking of a plant pathogen outbreak reveals rapid and successive, multidecade plasmid reduction.mSystems · 2024Article
- Article
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- Genetic manipulation of candidate phyla radiation bacteria provides functional insights into microbial dark matter.bioRxiv : the preprint server for biology · 2023Article
- Codon Usage Bias and Cluster Analysis of theGenetics research · 2022Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Bacterial genomes often reflect a bias in the usage of codons. These biases are often most notable within highly expressed genes. While deviations in codon usage can be attributed to selection or mutational biases, they can also be functional, for example controlling gene expression or guiding protein structure. Several different metrics have been developed to identify biases in codon usage. Previously we released a database, CBDB: The Codon Bias Database, in which users could retrieve precalculated codon bias data for bacterial RefSeq genomes. With the increase of bacterial genome sequence data since its release a new tool was needed. Here we present the Dynamic Codon Biaser (DCB) tool, a web application that dynamically calculates the codon usage bias statistics of prokaryotic genomes. DCB bases these calculations on 40 different highly expressed genes (HEGs) that are highly conserved across different prokaryotic species. A user can either specify an NCBI accession number or upload their own sequence. DCB returns both the bias statistics and the genome's HEG sequences. These calculations have several downstream applications, such as evolutionary studies and phage-host predictions. The source code is freely available, and the website is hosted at www.cbdb.info.
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