IMT Institutional Repository: No conditions. Results ordered -Date Deposited. 2024-03-28T20:25:46ZEPrintshttp://eprints.imtlucca.it/images/logowhite.pnghttp://eprints.imtlucca.it/2011-08-12T09:27:34Z2013-03-05T15:47:33Zhttp://eprints.imtlucca.it/id/eprint/812This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/8122011-08-12T09:27:34ZDNA as a medium for storing digital signalsMotivated by the storage capacity and efficiency of the DNA molecule in this paper we propose to utilize DNA molecules to store digital signals. We show that hybridization of DNA molecules can be used as a similarity criterion for retrieving digital signals encoded and stored in a DNA database. 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, similarly 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.Sotirios A. Tsaftarissotirios.tsaftaris@imtlucca.itVassily HatzimanikatiAggelos K. Katsaggelos2011-08-12T09:20:11Z2013-03-05T15:47:59Zhttp://eprints.imtlucca.it/id/eprint/811This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/8112011-08-12T09:20:11ZDNA hybridization as a similarity criterion for querying digital signals stored in DNA databasesWe 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.Sotirios A. Tsaftarissotirios.tsaftaris@imtlucca.itVassily HatzimanikatiAggelos K. Katsaggelos2011-08-10T13:39:35Z2013-03-05T15:48:37Zhttp://eprints.imtlucca.it/id/eprint/791This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/7912011-08-10T13:39:35ZIn silico estimation of annealing specificity of query searches in DNA databasesWe consider DNA implementations of databases for digital signals with retrieval and mining capabilities. Digital signals are encoded in DNA sequences and retrieved through annealing between query DNA primers and data carrying DNA target sequences. The hybridization between query and target can be non-specific containing multiple mismatches thus implementing similarity-based searches. In this paper we examine theoretically and by simulation the efficiency of such a system by estimating the concentrations of query-target duplex formations at equilibrium. A coupled kinetic model is used to estimate the concentrations. We offer a derivation that results in an equation that is guaranteed to have a solution and can be easily and accurately solved computationally with bi-section root-finding methods. Finally, we also provide an approximate solution at dilute query concentrations that results in a closed form expression. This expression is used to improve the speed of the bi-section algorithm and also to find a closed form expression for the specificity ratios.Sotirios A. Tsaftarissotirios.tsaftaris@imtlucca.itVassily HatzimanikatiAggelos K. Katsaggelos