Tsaftaris, Sotirios A. and Hatzimanikati, Vassily and Katsaggelos, Aggelos K. DNA hybridization as a similarity criterion for querying digital signals stored in DNA databases. In: International conference on acoustics, speech and signal processing. IEEE , II-II. ISBN 1-4244-0469-X (2006)Full text not available from this repository.
We demonstrate via simulation that hybridization of DNA molecules can be used as a similarity criterion for retrieving digital signals encoded and stored in a synthesized DNA database. After introducing some necessary DNA terminology, we briefly explain how digital signals are transformed to DNA sequences. Since retrieval is achieved through hybridization of query and data carrying DNA molecules, we present a mathematical model to estimate hybridization efficiency (also known as selectivity annealing). We show that selectivity annealing is inversely proportional to the mean squared error (MSE) of the encoded signal values. In addition, we show that the concentration of the molecules plays the same role as the decision threshold employed in digital signal matching algorithms. Finally, similar to the digital domain, we define a DNA signal-to-noise ratio (SNR) measure to assess the performance of the DNA-based retrieval scheme. Simulations are presented to validate our arguments.
|Item Type:||Book Section|
|Uncontrolled Keywords:||DNA databases; DNA hybridization; DNA sequences; MSE; SNR; digital signal matching algorithms; digital signals; mean squared error; selectivity annealing; signal-to-noise ratio; DNA; biology computing; database management systems; encoding; mean square error methods; pattern matching; sequences|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QH Natural history > QH426 Genetics
T Technology > TK Electrical engineering. Electronics Nuclear engineering
|Research Area:||Computer Science and Applications|
|Depositing User:||Users 35 not found.|
|Date Deposited:||12 Aug 2011 09:20|
|Last Modified:||05 Mar 2013 15:47|
Actions (login required)