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    • ENG: Bioinformatics: Scholarly Papers
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    •   OpenBU
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    • Bioinformatics
    • ENG: Bioinformatics: Scholarly Papers
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    Design of a Combinatorial DNA Microarray for Protein-DNA Interaction Studies

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    Copyright 2006 Mintseris and Eisen; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Date Issued
    2006-10-3
    Publisher Version
    10.1186/1471-2105-7-429
    Author(s)
    Mintseris, Julian
    Eisen, Michael B.
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    Permanent Link
    https://hdl.handle.net/2144/3193
    Citation (published version)
    Mintseris, Julian, Michael B Eisen. "Design of a combinatorial DNA microarray for protein-DNA interaction studies" BMC Bioinformatics 7:429. (2006)
    Abstract
    BACKGROUND. Discovery of precise specificity of transcription factors is an important step on the way to understanding the complex mechanisms of gene regulation in eukaryotes. Recently, double-stranded protein-binding microarrays were developed as a potentially scalable approach to tackle transcription factor binding site identification. RESULTS. Here we present an algorithmic approach to experimental design of a microarray that allows for testing full specificity of a transcription factor binding to all possible DNA binding sites of a given length, with optimally efficient use of the array. This design is universal, works for any factor that binds a sequence motif and is not species-specific. Furthermore, simulation results show that data produced with the designed arrays is easier to analyze and would result in more precise identification of binding sites. CONCLUSION. In this study, we present a design of a double stranded DNA microarray for protein-DNA interaction studies and show that our algorithm allows optimally efficient use of the arrays for this purpose. We believe such a design will prove useful for transcription factor binding site identification and other biological problems.
    Rights
    Copyright 2006 Mintseris and Eisen; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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    • ENG: Bioinformatics: Scholarly Papers [101]


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