ReviewFrontiers in bioengineering and biotechnology2014
Computational tools and algorithms for designing customized synthetic genes.
Review in Frontiers in bioengineering and biotechnology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- Integrated immunoinformatics for the design of novel multi-epitope vaccine and identification of new drug targets against Stenotrophomonas maltophilia, a multidrug-resistant superbug.Journal, genetic engineering & biotechnology · 2026Article
- Gradient-based optimization for mRNA sequence design.Bioinformatics (Oxford, England) · 2026Article
- Innovative multi-epitope vaccine engineering for dual protection against Salmonella and Shigella leveraging FliC flagellin protein adjuvant properties: an immunoinformatics-based approach.Journal of translational medicine · 2026Article
- Comparative Analysis of Codon Optimization Tools: Advancing toward a Multi-Criteria Framework for Synthetic Gene Design.Journal of microbiology and biotechnology · 2025Article
- BAC-browser: the tool for synthetic biology.BMC bioinformatics · 2025Article
- Development of a multi-epitope vaccine from outer membrane proteins and identification of novel drug targets againstFrontiers in immunology · 2025Article
- Leveraging computer-aided design and artificial intelligence to develop a next-generation multi-epitope tuberculosis vaccine candidate.Infectious medicine · 2024Article
- Molecular targets and strategies in the development of nucleic acid cancer vaccines: from shared to personalized antigens.Journal of biomedical science · 2024Review
- mRNAid, an open-source platform for therapeutic mRNA design and optimization strategies.NAR genomics and bioinformatics · 2024Article
- An exploratory in silico comparison of open-source codon harmonization tools.Microbial cell factories · 2023Article
- Protein-Based Biological Materials: Molecular Design and Artificial Production.Chemical reviews · 2023Review
- Using protein-per-mRNA differences among human tissues in codon optimization.Genome biology · 2023Article
- Developing a multiepitope vaccine for the prevention of SARS-CoV-2 and monkeypox virus co-infection: A reverse vaccinology analysis.International immunopharmacology · 2023Article
- gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.Frontiers in molecular biosciences · 2023Article
- Controlling gene expression with deep generative design of regulatory DNA.Nature communications · 2022Article
- Structural, functional, and immunogenicity implications of F9 gene recoding.Blood advances · 2022Article
- Design of typical genes for heterologous gene expression.Scientific reports · 2022Article
- In silico screening and heterologous expression of soluble dimethyl sulfide monooxygenases of microbial origin in Escherichia coli.Applied microbiology and biotechnology · 2022Article
- Article
- Codon usage bias.Molecular biology reports · 2022Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.
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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.