ArticleBMC bioinformatics2024
GenRCA: a user-friendly rare codon analysis tool for comprehensive evaluation of codon usage preferences based on coding sequences in genomes.
Article in BMC bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Transgene sequence codon optimization and composition determines replication competence of self-amplifying RNA.Molecular therapy : the journal of the American Society of Gene Therapy · 2026Article
- AssessingJournal of fungi (Basel, Switzerland) · 2026Article
- High-level expression of full-length human CYP2E1 in Escherichia coli: Comparison of full-length human CYP2E1 to truncated counterpart shows enhanced association with redox partners.Drug metabolism and disposition: the biological fate of chemicals · 2026Article
- Pichia-CLM: A language model-based codon optimization pipeline forProceedings of the National Academy of Sciences of the United States of America · 2026Article
- Design and in silico evaluation of an mRNA vaccine against HTLV-1 using AI-driven reverse vaccinology approaches.PloS one · 2026Article
- Codon Usage Bias of the Polyphenol Oxidase Genes inPlants (Basel, Switzerland) · 2025Article
- Targeting Streptococcus pyogenes atpF protein for multi-epitope vaccine development: a genomics-driven immunoinformatics strategy.Journal, genetic engineering & biotechnology · 2025Article
- Design of a multi-epitope vaccine candidate against Vibrio cholerae.Scientific reports · 2025Article
- A deep learning model trained on expressed transcripts across different tissue types reveals cell-type codon-optimization preferences.Nucleic acids research · 2025Article
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Authors and funding
4 authors.
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Abstract
backgroundThe study of codon usage bias is important for understanding gene expression, evolution and gene design, providing critical insights into the molecular processes that govern the function and regulation of genes. Codon Usage Bias (CUB) indices are valuable metrics for understanding codon usage patterns across different organisms without extensive experiments. Considering that there is no one-fits-all index for all species, a comprehensive platform supporting the calculation and analysis of multiple CUB indices for codon optimization is greatly needed.
resultsHere, we release GenRCA, an updated version of our previous Rare Codon Analysis Tool, as a free and user-friendly website for all-inclusive evaluation of codon usage preferences of coding sequences. In this study, we manually reviewed and implemented up to 31 codon preference indices, with 65 expression host organisms covered and batch processing of multiple gene sequences supported, aiming to improve the user experience and provide more comprehensive and efficient analysis.
conclusionsOur website fills a gap in the availability of comprehensive tools for species-specific CUB calculations, enabling researchers to thoroughly assess the protein expression level based on a comprehensive list of 31 indices and further guide the codon optimization.
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Registered trials
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