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When planning heterologous expression of a gene, it is necessary to assess the number of rare codons that can be encountered in the gene. This program helps you find out.



Related Projects


codonPhyML uses Markovian codon models of evolution in phylogeny reconstruction. Given a set of species characterized by their DNA sequences as input, codonPhyML will return the phylogenetic tree that best describes their evolutionary relationship. Our paper describing codonPhyML has been published in the journal quot;Molecular Biology and Evolutionquot; (MBE). For more details, follow the link: codonPhyML is on the cover of MBE! Check this


CodonW is a programme designed to simplify the Multivariate analysis (correspondence analysis) of codon and amino acid usage. It was written in ANSI compliant C. See the README file for more information.


EvoRadical was written in C. It implements a new codon-based likelihood models for detecting site-specific selection pressures acting on specific physicochemical properties.

Theframeshiftkids - Keepin' track o' frameshift code (Beached Whale Frameshift)

Click below for good times by Hao Lian (shadytrees), Vivek Bhattacharya (nemosupport), and Daniel Vitek (drvitek), second place winners in the national Siemens Competition. You can download our presentation at the right. You can read the paper describing our model in lustrous detail with full references to biological literature as well as a cursory synthesis of physics, biology, mathematics, and angst. GSPtools is documented within the work-in-progress manual. NewsSee Changelog for details. Apri

Rcclust - Rare Codon Cluster Analysis Tool

A UNIX-based, web-accessible tool to enable analysis of synonymous codon distributions in human genes, and the effects of known disease-causing SNPs on these distributions.

Pynchon - containers for (not only) biological data in numpy arrays

Pynchon - containers (not only) for biological data in numpy arrays.Pynchon provides data-container objects built by sub-classing numpy arrays. These sub-classes can be manipulated in exactly the same way as numpy.ndarray instances, but additionally provide support for: data-type specific methods. easy construction from specific inputs with magical broadcasting. input validation. easy compressed dumping and loading. uniform support for rank-0 arrays and structured data-types. Some classes are sp

Jacusi - Codon Adaptation

Java implementation of CUSI tool