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. 2004 Sep 22;20(14):2329-30.
doi: 10.1093/bioinformatics/bth238. Epub 2004 Apr 1.

INCA: synonymous codon usage analysis and clustering by means of self-organizing map

Fran Supek  1 , Kristian Vlahovicek
Affiliations

INCA: synonymous codon usage analysis and clustering by means of self-organizing map

Fran Supek et al. Bioinformatics. .

Abstract

INteractive Codon usage Analysis (INCA) provides an array of features useful in analysis of synonymous codon usage in whole genomes. In addition to computing codon frequencies and several usage indices, such as 'codon bias', effective Nc and CAI, the primary strength of INCA has numerous options for the interactive graphical display of calculated values, thus allowing visual detection of various trends in codon usage. Finally, INCA includes a specific unsupervised neural network algorithm, the self-organizing map, used for gene clustering according to the preferred utilization of codons.

Availability: INCA is available for the Win32 platform and is free of charge for academic use. For details, visit the web page http://www.bioinfo-hr.org/inca or contact the author directly.

Supplementary information: Software is accompanied with a user manual and a short tutorial.

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