Title |
ATGme: Open-source web application for rare codon identification and custom DNA sequence optimization
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Published in |
BMC Bioinformatics, September 2015
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DOI | 10.1186/s12859-015-0743-5 |
Pubmed ID | |
Authors |
Edward Daniel, Goodluck U. Onwukwe, Rik K. Wierenga, Susan E. Quaggin, Seppo J. Vainio, Mirja Krause |
Abstract |
Codon usage plays a crucial role when recombinant proteins are expressed in different organisms. This is especially the case if the codon usage frequency of the organism of origin and the target host organism differ significantly, for example when a human gene is expressed in E. coli. Therefore, to enable or enhance efficient gene expression it is of great importance to identify rare codons in any given DNA sequence and subsequently mutate these to codons which are more frequently used in the expression host. We describe an open-source web-based application, ATGme, which can in a first step identify rare and highly rare codons from most organisms, and secondly gives the user the possibility to optimize the sequence. This application provides a simple user-friendly interface utilizing three optimization strategies: 1. one-click optimization, 2. bulk optimization (by codon-type), 3. individualized custom (codon-by-codon) optimization. ATGme is an open-source application which is freely available at: http://atgme.org. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Canada | 1 | 25% |
Italy | 1 | 25% |
Unknown | 2 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 3 | 75% |
Scientists | 1 | 25% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United Kingdom | 1 | 1% |
Unknown | 97 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 16 | 16% |
Student > Master | 16 | 16% |
Researcher | 14 | 14% |
Student > Bachelor | 9 | 9% |
Other | 5 | 5% |
Other | 11 | 11% |
Unknown | 27 | 28% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 23 | 23% |
Agricultural and Biological Sciences | 23 | 23% |
Computer Science | 5 | 5% |
Immunology and Microbiology | 3 | 3% |
Chemical Engineering | 3 | 3% |
Other | 11 | 11% |
Unknown | 30 | 31% |