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Investigation of DNA Sequences Utilizing Frequency-Selective Nanopore Structures

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Bioinformatics and Biomedical Engineering (IWBBIO 2017)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10209))

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Abstract

Newer methodologies that are quick, label-free, reliable, and low-cost for DNA sequencing and identification are currently being explored. High frequency based-scattering parameters provide a reliable measurement platform and technique to characterize DNA bases. Using a modeling approach, this work investigates the utilization of high frequency-selective structure coupled with nanopore technology for nucleotide identification and sequencing. The model envisions a coplanar waveguide structure harboring a small hole with an internal diameter of the order of several nanometers to demonstrate the potential use of high frequency to identify and sequence DNA. When DNA molecule enters the pore, it should cause disturbance in the electromagnetic field. This disturbance should result in a shift in the resonance frequency and its corresponding characteristics, thus enabling nucleotide identification. The frequency response of four different single DNA strands composed exclusively of either A, C, G or T were measured and characterized to extract the corresponding dielectric constants and their corresponding base paired strands. These dielectric constant values were then used to model the presence of the corresponding DNA molecules in the nanopore. The conducted simulations revealed distinctions between the single and double-stranded DNA molecules due to their different and distinct electrical properties.

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Acknowledgment

This work was supported by funds from UAEU Sheikh Zayed Center for Health Science to MA and the Start-Up funds from UAEU to FM.

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Correspondence to Ali Hilal-Alnaqbi .

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Hilal-Alnaqbi, A., Ahmad, M.A., Rizvi, T.A., Mustafa, F. (2017). Investigation of DNA Sequences Utilizing Frequency-Selective Nanopore Structures. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2017. Lecture Notes in Computer Science(), vol 10209. Springer, Cham. https://doi.org/10.1007/978-3-319-56154-7_1

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  • DOI: https://doi.org/10.1007/978-3-319-56154-7_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56153-0

  • Online ISBN: 978-3-319-56154-7

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