The Complexity and Viability of DNA Computations.
Conference: Biocomputing and emergent computation: Proceedings of BCEC97
Article: Microflow BioMolecular Computation[Show abstract] [Hide abstract]
ABSTRACT: In this paper we provide a model for micro-flow based bio-molecular computation (MFBMC). It provides an abstraction for the design of algorithms which account for the constraintsof the model. Our MF-BMC model uses abstractions of both the recombinant DNA (RDNA)technology as well as of the micro-flow technology and takes into account both of their limitations.
Conference Paper: A DNA-based simulation model for bounded fan-in Boolean circuits[Show abstract] [Hide abstract]
ABSTRACT: DNA computing has recently gained intensive attention as an emerging field bridging the gap between computer science and biomolecular science. DNA based computing can be competitively used to simulate various computing models including Boolean circuits because of its potential to offer massive parallelism. In this paper we present a new DNA-based evaluation algorithm for a bounded fan-in circuit consisting of AND and OR gates. The proposed model employs standard bio-molecular techniques. The main advantage of our method is that each level of circuit is capable of containing both AND and OR gates. It is shown that large bounded fan-in circuits can be simulated by the proposed approach with a logarithmic slowdown in computation time.Proceedings of the 10th WSEAS international conference on Computers; 07/2006
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ABSTRACT: We p resent, in this paper ,ad etailed translation from algorithms implemented on a standard model of paral- lel computation — the CREW PRAM — to DNA-based methods. Our translation is efficient in the follow- ing sense: if A is a PRAM algorithm using P (n )p rocessors, S (n )s pace, and taking T (n )t ime then the total volume of DN Au sed is O ( P (n) T (n) S (n )l ogS (n )) ;f urthermore, the total computation time of the DNA algorithm is bounded by O ( T (n )l ogS (n )) .A sac onsequence our methods give a direct translation from any NC algorithm into an effective DNA algorithm. 1. Intr oduction
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